Skip to main content
Erschienen in:

31.05.2024

Filtering-Based Bias-Compensation Recursive Estimation Algorithm for an Output Error Model with Colored Noise

verfasst von: Zhenwei Shi, Lincheng Zhou, Haodong Yang, Xiangli Li, Mei Dai

Erschienen in: Circuits, Systems, and Signal Processing | Ausgabe 9/2024

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

For the output error (OE) models whose outputs are contaminated by colored process noises (i.e., correlated noises), this paper derives a new form of bias compensation recursive least squares (BCRLS) algorithm by means of the data filtering technology and the bias compensation principle. The basic idea is to firstly transform the OE model disturbed by colored process noise into a simple OE model with the white noise by adopting the data filtering technology at each recursive calculation, and then to calculate the bias compensation term, based on the new OE model with the bias-compensation technique. Finally, eliminate this bias term in the biased RLS parameter estimation of the OE model to be identified, thereby achieving its unbiased parameter estimation. Unlike the previous BCRLS algorithm, this algorithm can still achieve unbiased parameter estimation of OE systems in the presence of colored process noise without calculating complex noise correlation functions. The performance of the proposed algorithm is demonstrated through three digital simulation examples.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

ATZelektronik

Die Fachzeitschrift ATZelektronik bietet für Entwickler und Entscheider in der Automobil- und Zulieferindustrie qualitativ hochwertige und fundierte Informationen aus dem gesamten Spektrum der Pkw- und Nutzfahrzeug-Elektronik. 

Lassen Sie sich jetzt unverbindlich 2 kostenlose Ausgabe zusenden.

ATZelectronics worldwide

ATZlectronics worldwide is up-to-speed on new trends and developments in automotive electronics on a scientific level with a high depth of information. 

Order your 30-days-trial for free and without any commitment.

Weitere Produktempfehlungen anzeigen
Literatur
1.
Zurück zum Zitat S. An, Y. He, L.J. Wang, Maximum likelihood based multi-innovation stochastic gradient identification algorithms for bilinear stochastic systems with ARMA noise. Int. J. Adapt. Control Signal Process. 37(10), 2690–2705 (2023)MathSciNet S. An, Y. He, L.J. Wang, Maximum likelihood based multi-innovation stochastic gradient identification algorithms for bilinear stochastic systems with ARMA noise. Int. J. Adapt. Control Signal Process. 37(10), 2690–2705 (2023)MathSciNet
2.
Zurück zum Zitat Y. Bai, B. Yan, C. Zhou, T. Su, X. Jin, State of art on state estimation: Kalman filter driven by machine learning. Annu. Rev. Control. 56, 100909 (2023)MathSciNet Y. Bai, B. Yan, C. Zhou, T. Su, X. Jin, State of art on state estimation: Kalman filter driven by machine learning. Annu. Rev. Control. 56, 100909 (2023)MathSciNet
3.
Zurück zum Zitat P. Bernard, V. Andrieu, D. Astolfi, Observer design for continuous-time dynamical systems. Annu. Rev. Control. 53, 224–248 (2022)MathSciNet P. Bernard, V. Andrieu, D. Astolfi, Observer design for continuous-time dynamical systems. Annu. Rev. Control. 53, 224–248 (2022)MathSciNet
4.
Zurück zum Zitat Y.Q. Bi, Y. Ji, Parameter estimation of fractional-order Hammerstein state space system based on the extended Kalman filter. Int. J. Adapt. Control Signal Process. 37(7), 1827–1846 (2023) Y.Q. Bi, Y. Ji, Parameter estimation of fractional-order Hammerstein state space system based on the extended Kalman filter. Int. J. Adapt. Control Signal Process. 37(7), 1827–1846 (2023)
5.
Zurück zum Zitat Y. Cao, Y. An, S. Su et al., A statistical study of railway safety in China and Japan 1990–2020. Accid. Anal. Prevent. 175, 106764 (2022) Y. Cao, Y. An, S. Su et al., A statistical study of railway safety in China and Japan 1990–2020. Accid. Anal. Prevent. 175, 106764 (2022)
6.
Zurück zum Zitat Y. Cao, Y.S. Ji, Y.K. Sun, S. Su, The fault diagnosis of a switch machine based on deep random forest fusion. IEEE Intell. Transp. Syst. Mag. 15(1), 437–452 (2023) Y. Cao, Y.S. Ji, Y.K. Sun, S. Su, The fault diagnosis of a switch machine based on deep random forest fusion. IEEE Intell. Transp. Syst. Mag. 15(1), 437–452 (2023)
7.
Zurück zum Zitat Y. Cao, L.C. Ma, S. Xiao et al., Standard analysis for transfer delay in CTCS-3. Chin. J. Electron. 26(5), 1057–1063 (2017) Y. Cao, L.C. Ma, S. Xiao et al., Standard analysis for transfer delay in CTCS-3. Chin. J. Electron. 26(5), 1057–1063 (2017)
8.
Zurück zum Zitat Y. Cao, Y.K. Sun, G. Xie, P. Li, A sound-based fault diagnosis method for railway point machines based on two-stage feature selection strategy and ensemble classifier. IEEE Trans. Intell. Transp. Syst. 23(8), 12074–12083 (2022) Y. Cao, Y.K. Sun, G. Xie, P. Li, A sound-based fault diagnosis method for railway point machines based on two-stage feature selection strategy and ensemble classifier. IEEE Trans. Intell. Transp. Syst. 23(8), 12074–12083 (2022)
9.
Zurück zum Zitat Y. Cao, Y.K. Sun, G. Xie, T. Wen, Fault diagnosis of train plug door based on a hybrid criterion for IMFs selection and fractional wavelet package energy entropy. IEEE Trans. Veh. Technol. 68(8), 7544–7551 (2019) Y. Cao, Y.K. Sun, G. Xie, T. Wen, Fault diagnosis of train plug door based on a hybrid criterion for IMFs selection and fractional wavelet package energy entropy. IEEE Trans. Veh. Technol. 68(8), 7544–7551 (2019)
10.
Zurück zum Zitat Y. Cao, Z. Wang, F. Liu, P. Li, G. Xie, Bio-inspired speed curve optimization and sliding mode tracking control for subway trains. IEEE Trans. Veh. Technol. 68(7), 6331–6342 (2019) Y. Cao, Z. Wang, F. Liu, P. Li, G. Xie, Bio-inspired speed curve optimization and sliding mode tracking control for subway trains. IEEE Trans. Veh. Technol. 68(7), 6331–6342 (2019)
11.
Zurück zum Zitat Y. Cao, J.K. Wen, A. Hobiny, P. Li, T. Wen, Parameter-varying artificial potential field control of virtual coupling system with nonlinear dynamics. Fractals 30(2), 2240099 (2022) Y. Cao, J.K. Wen, A. Hobiny, P. Li, T. Wen, Parameter-varying artificial potential field control of virtual coupling system with nonlinear dynamics. Fractals 30(2), 2240099 (2022)
12.
Zurück zum Zitat Y. Cao, J.K. Wen, L.C. Ma, Tracking and collision avoidance of virtual coupling train control system. Alex. Eng. J. 60(2), 2115–2125 (2021) Y. Cao, J.K. Wen, L.C. Ma, Tracking and collision avoidance of virtual coupling train control system. Alex. Eng. J. 60(2), 2115–2125 (2021)
13.
Zurück zum Zitat Y. Cao, Y.R. Yang, L.C. Ma et al., Research on virtual coupled train control method based on GPC & VAPF. Chin. J. Electron. 31(5), 897–905 (2022) Y. Cao, Y.R. Yang, L.C. Ma et al., Research on virtual coupled train control method based on GPC & VAPF. Chin. J. Electron. 31(5), 897–905 (2022)
14.
Zurück zum Zitat Y. Cao, Z.X. Zhang, F.L. Cheng, S. Su, Trajectory optimization for high-speed trains via a mixed integer linear programming approach. IEEE Trans. Intell. Transp. Syst. 23(10), 17666–17676 (2022) Y. Cao, Z.X. Zhang, F.L. Cheng, S. Su, Trajectory optimization for high-speed trains via a mixed integer linear programming approach. IEEE Trans. Intell. Transp. Syst. 23(10), 17666–17676 (2022)
15.
Zurück zum Zitat Y. Chang, F. ZHou, H. Yan, W. Huang, G. Luo, Noise and interference suppression control method of DC-DC buck converters based on cascaded filter LADRC. Int. J. Control Autom. Syst. 22(5), 1526–1536 (2024) Y. Chang, F. ZHou, H. Yan, W. Huang, G. Luo, Noise and interference suppression control method of DC-DC buck converters based on cascaded filter LADRC. Int. J. Control Autom. Syst. 22(5), 1526–1536 (2024)
16.
Zurück zum Zitat J. Chen, Y. Pu, L.X. Guo, Second-order optimization methods for time-delay autoregressive exogenous models: nature gradient descent method and its two modified methods. Int. J. Adapt. Control Signal Process. 37(1), 211–223 (2023)MathSciNet J. Chen, Y. Pu, L.X. Guo, Second-order optimization methods for time-delay autoregressive exogenous models: nature gradient descent method and its two modified methods. Int. J. Adapt. Control Signal Process. 37(1), 211–223 (2023)MathSciNet
17.
Zurück zum Zitat J. Chen, Q.M. Zhu, Y.J. Liu, Modified Kalman filtering based multi-step-length gradient iterative algorithm for ARX models with random missing outputs. Automatica 118, 109034 (2020)MathSciNet J. Chen, Q.M. Zhu, Y.J. Liu, Modified Kalman filtering based multi-step-length gradient iterative algorithm for ARX models with random missing outputs. Automatica 118, 109034 (2020)MathSciNet
18.
Zurück zum Zitat F. Ding, System Identification-New Theory and Methods (Science Press, Beijing, 2013) F. Ding, System Identification-New Theory and Methods (Science Press, Beijing, 2013)
19.
Zurück zum Zitat F. Ding, System Identification-Performances Analysis for Identification Methods (Science Press, Beijing, 2014) F. Ding, System Identification-Performances Analysis for Identification Methods (Science Press, Beijing, 2014)
20.
Zurück zum Zitat F. Ding, System Identification-Auxiliary Model Identification Idea and Methods (Science Press, Beijing, 2017) F. Ding, System Identification-Auxiliary Model Identification Idea and Methods (Science Press, Beijing, 2017)
21.
Zurück zum Zitat F. Ding, System Identification-Iterative Search Principle and Identification Methods (Science Press, Beijing, 2018) F. Ding, System Identification-Iterative Search Principle and Identification Methods (Science Press, Beijing, 2018)
22.
Zurück zum Zitat F. Ding, System Identification-Multi-Innovation Identification Theory and Methods (Science Press, Beijing, 2016) F. Ding, System Identification-Multi-Innovation Identification Theory and Methods (Science Press, Beijing, 2016)
23.
Zurück zum Zitat J. Ding, Bias compensation-based parameter estimation for output error moving average systems. Int. J. Adapt. Control Signal Process. 25(12), 1100–1111 (2011)MathSciNet J. Ding, Bias compensation-based parameter estimation for output error moving average systems. Int. J. Adapt. Control Signal Process. 25(12), 1100–1111 (2011)MathSciNet
24.
Zurück zum Zitat F. Ding, Least squares parameter estimation and multi-innovation least squares methods for linear fitting problems from noisy data. J. Comput. Appl. Math. 426, 115107 (2023)MathSciNet F. Ding, Least squares parameter estimation and multi-innovation least squares methods for linear fitting problems from noisy data. J. Comput. Appl. Math. 426, 115107 (2023)MathSciNet
25.
Zurück zum Zitat F. Ding, T. Chen, L. Qiu, Bias compensation based recursive least squares identification algorithm for MISO systems. IEEE Trans. Circuits Syst. II Express Briefs 53(5), 349–353 (2006) F. Ding, T. Chen, L. Qiu, Bias compensation based recursive least squares identification algorithm for MISO systems. IEEE Trans. Circuits Syst. II Express Briefs 53(5), 349–353 (2006)
26.
Zurück zum Zitat F. Ding, L. Lv, J. Pan, Two-stage gradient-based iterative estimation methods for controlled autoregressive systems using the measurement data. Int. J. Control Autom. Syst. 18(4), 886–896 (2020) F. Ding, L. Lv, J. Pan, Two-stage gradient-based iterative estimation methods for controlled autoregressive systems using the measurement data. Int. J. Control Autom. Syst. 18(4), 886–896 (2020)
27.
Zurück zum Zitat F. Ding, H. Ma, J. Pan, E.F. Yang, Hierarchical gradient- and least squares-based iterative algorithms for input nonlinear output-error systems using the key term separation. J. Frankl. Inst. 358(9), 5113–5135 (2021)MathSciNet F. Ding, H. Ma, J. Pan, E.F. Yang, Hierarchical gradient- and least squares-based iterative algorithms for input nonlinear output-error systems using the key term separation. J. Frankl. Inst. 358(9), 5113–5135 (2021)MathSciNet
28.
Zurück zum Zitat F. Ding, X. Shao, L. Xu, X. Zhang, H. Xu, Y. Zhou, Filtered generalized iterative parameter identification for equation-error autoregressive models based on the filtering identification idea. Int. J. Adapt. Control Signal Process. 38(4), 1363–1385 (2024)MathSciNet F. Ding, X. Shao, L. Xu, X. Zhang, H. Xu, Y. Zhou, Filtered generalized iterative parameter identification for equation-error autoregressive models based on the filtering identification idea. Int. J. Adapt. Control Signal Process. 38(4), 1363–1385 (2024)MathSciNet
29.
Zurück zum Zitat F. Ding, L. Xu, X. Zhang, H. Ma, Hierarchical gradient- and least squares-based iterative estimation algorithms for input-nonlinear output-error systems by using the over-parameterization. Int. J. Robust Nonlinear Control 34(2), 1120–1147 (2024) F. Ding, L. Xu, X. Zhang, H. Ma, Hierarchical gradient- and least squares-based iterative estimation algorithms for input-nonlinear output-error systems by using the over-parameterization. Int. J. Robust Nonlinear Control 34(2), 1120–1147 (2024)
30.
Zurück zum Zitat F. Ding, L. Xu, X. Zhang, Y. Zhou, Filtered auxiliary model recursive generalized extended parameter estimation methods for Box-Jenkins systems by means of the filtering identification idea. Int. J. Robust Nonlinear Control 33(10), 5510–5535 (2023)MathSciNet F. Ding, L. Xu, X. Zhang, Y. Zhou, Filtered auxiliary model recursive generalized extended parameter estimation methods for Box-Jenkins systems by means of the filtering identification idea. Int. J. Robust Nonlinear Control 33(10), 5510–5535 (2023)MathSciNet
31.
Zurück zum Zitat F. Ding, L. Xu, X. Zhang, Y. Zhou, X. Luan, Recursive identification methods for general stochastic systems with colored noises by using the hierarchical identification principle and the filtering identification idea. Annu. Rev. Control. 57, 100942 (2024)MathSciNet F. Ding, L. Xu, X. Zhang, Y. Zhou, X. Luan, Recursive identification methods for general stochastic systems with colored noises by using the hierarchical identification principle and the filtering identification idea. Annu. Rev. Control. 57, 100942 (2024)MathSciNet
32.
Zurück zum Zitat R. Diversi, A. Tilli, A. Bartolini, F. Beneventi, L. Benini, Bias-compensated least squares identification of distributed thermal models for many-core systems-on-chip. IEEE Trans. Circuits Syst. I Regular Pap. 61(9), 2663–2676 (2014) R. Diversi, A. Tilli, A. Bartolini, F. Beneventi, L. Benini, Bias-compensated least squares identification of distributed thermal models for many-core systems-on-chip. IEEE Trans. Circuits Syst. I Regular Pap. 61(9), 2663–2676 (2014)
33.
Zurück zum Zitat D. Dong, I.R. Petersen, Quantum estimation, control and learning: opportunities and challenges. Annu. Rev. Control. 54, 243–251 (2022)MathSciNet D. Dong, I.R. Petersen, Quantum estimation, control and learning: opportunities and challenges. Annu. Rev. Control. 54, 243–251 (2022)MathSciNet
34.
Zurück zum Zitat Y.M. Fan, X.M. Liu, Two-stage auxiliary model gradient-based iterative algorithm for the input nonlinear controlled autoregressive system with variable-gain nonlinearity. Int. J. Robust Nonlinear Control 30(14), 5492–5509 (2020)MathSciNet Y.M. Fan, X.M. Liu, Two-stage auxiliary model gradient-based iterative algorithm for the input nonlinear controlled autoregressive system with variable-gain nonlinearity. Int. J. Robust Nonlinear Control 30(14), 5492–5509 (2020)MathSciNet
35.
Zurück zum Zitat Y.M. Fan, X.M. Liu, Auxiliary model-based multi-innovation recursive identification algorithms for an input nonlinear controlled autoregressive moving average system with variable-gain nonlinearity. Int. J. Adapt. Control Signal Process. 36(3), 521–540 (2022)MathSciNet Y.M. Fan, X.M. Liu, Auxiliary model-based multi-innovation recursive identification algorithms for an input nonlinear controlled autoregressive moving average system with variable-gain nonlinearity. Int. J. Adapt. Control Signal Process. 36(3), 521–540 (2022)MathSciNet
36.
Zurück zum Zitat R. Gehlhar, M. Tucker, A.D. Ames, A review of current state-of-the-art control methods for lower-limb powered prostheses. Annu. Rev. Control. 55, 142–164 (2023)MathSciNet R. Gehlhar, M. Tucker, A.D. Ames, A review of current state-of-the-art control methods for lower-limb powered prostheses. Annu. Rev. Control. 55, 142–164 (2023)MathSciNet
37.
Zurück zum Zitat M. Gilson, P. Van den Hof, On the relation between a bias-eliminated least-squares (BELS) and an IV estimator in closed-loop identification. Automatica 37(10), 1593–1600 (2001) M. Gilson, P. Van den Hof, On the relation between a bias-eliminated least-squares (BELS) and an IV estimator in closed-loop identification. Automatica 37(10), 1593–1600 (2001)
38.
Zurück zum Zitat Y. Gu, W. Dai, Q. Zhu, H. Nouri, Hierarchical multi-innovation stochastic gradient identification algorithm for estimating a bilinear state-space model with moving average noise. J. Comput. Appl. Math. 420, 114794 (2023)MathSciNet Y. Gu, W. Dai, Q. Zhu, H. Nouri, Hierarchical multi-innovation stochastic gradient identification algorithm for estimating a bilinear state-space model with moving average noise. J. Comput. Appl. Math. 420, 114794 (2023)MathSciNet
39.
Zurück zum Zitat Y. Gu, Q.M. Zhu, H. Nouri, Identification and U-control of a state-space system with time-delay. Int. J. Adapt. Control Signal Process. 36(1), 138–154 (2022)MathSciNet Y. Gu, Q.M. Zhu, H. Nouri, Identification and U-control of a state-space system with time-delay. Int. J. Adapt. Control Signal Process. 36(1), 138–154 (2022)MathSciNet
40.
Zurück zum Zitat J. Hou, Parsimonious model based consistent subspace identification of Hammerstein systems under periodic disturbances. Int. J. Control Autom. Syst. 22(1), 61–71 (2024) J. Hou, Parsimonious model based consistent subspace identification of Hammerstein systems under periodic disturbances. Int. J. Control Autom. Syst. 22(1), 61–71 (2024)
41.
Zurück zum Zitat J. Hou, F. Chen, P. Li et al., Gray-box parsimonious subspace identification of Hammerstein-type systems. IEEE Trans. Ind. Electron. 68(10), 9941–9951 (2021) J. Hou, F. Chen, P. Li et al., Gray-box parsimonious subspace identification of Hammerstein-type systems. IEEE Trans. Ind. Electron. 68(10), 9941–9951 (2021)
42.
Zurück zum Zitat J. Hou, J.W. Liu, F.W. Chen et al., Robust lithium-ion state-of-charge and battery parameters joint estimation based on an enhanced adaptive unscented Kalman filter. Energy 271(15), 126998 (2023) J. Hou, J.W. Liu, F.W. Chen et al., Robust lithium-ion state-of-charge and battery parameters joint estimation based on an enhanced adaptive unscented Kalman filter. Energy 271(15), 126998 (2023)
43.
Zurück zum Zitat J. Hou, H.R. Wang, H. Su et al., A bias-correction modeling method of Hammerstein-Wiener systems with polynomial nonlinearities using noisy measurements. Mech. Syst. Signal Process. 213, 111329 (2024) J. Hou, H.R. Wang, H. Su et al., A bias-correction modeling method of Hammerstein-Wiener systems with polynomial nonlinearities using noisy measurements. Mech. Syst. Signal Process. 213, 111329 (2024)
44.
Zurück zum Zitat J. Hou, H. Su, C. Yu et al., Bias-correction errors-in-variables Hammerstein model identification. IEEE Trans. Ind. Electron. 70(7), 7268–7279 (2023) J. Hou, H. Su, C. Yu et al., Bias-correction errors-in-variables Hammerstein model identification. IEEE Trans. Ind. Electron. 70(7), 7268–7279 (2023)
45.
Zurück zum Zitat J. Hou, H. Su, C. Yu et al., Consistent subspace identification of errors-in-variables Hammerstein systems. IEEE Trans. Syst. Man Cybern. Syst. 53(4), 2292–2303 (2023) J. Hou, H. Su, C. Yu et al., Consistent subspace identification of errors-in-variables Hammerstein systems. IEEE Trans. Syst. Man Cybern. Syst. 53(4), 2292–2303 (2023)
46.
Zurück zum Zitat C. Hu, Y. Ji, Filtering-based gradient joint identification algorithms for nonlinear fractional-order models with colored noises. Commun. Nonlinear Sci. Numer. Simul. 130, 107759 (2024)MathSciNet C. Hu, Y. Ji, Filtering-based gradient joint identification algorithms for nonlinear fractional-order models with colored noises. Commun. Nonlinear Sci. Numer. Simul. 130, 107759 (2024)MathSciNet
47.
Zurück zum Zitat C. Hu, Y. Ji, C.Q. Ma, Joint two-stage multi-innovation recursive least squares parameter and fractional-order estimation algorithm for the fractional-order input nonlinear output-error autoregressive model. Int. J. Adapt. Control Signal Process. 37(7), 1650–1670 (2023)MathSciNet C. Hu, Y. Ji, C.Q. Ma, Joint two-stage multi-innovation recursive least squares parameter and fractional-order estimation algorithm for the fractional-order input nonlinear output-error autoregressive model. Int. J. Adapt. Control Signal Process. 37(7), 1650–1670 (2023)MathSciNet
48.
Zurück zum Zitat C. Hu, H.B. Liu, Y. Ji, Parameter and order estimation algorithms and convergence analysis for lithium-ion batteries. Int. J. Robust Nonlinear Control 33(18), 11411–11433 (2023)MathSciNet C. Hu, H.B. Liu, Y. Ji, Parameter and order estimation algorithms and convergence analysis for lithium-ion batteries. Int. J. Robust Nonlinear Control 33(18), 11411–11433 (2023)MathSciNet
49.
Zurück zum Zitat Y. Ji, A.N. Jiang, Filtering-based accelerated estimation approach for generalized time-varying systems with disturbances and colored noises. IEEE Trans. Circuits Syst. II Express Briefs 70(1), 206–210 (2023) Y. Ji, A.N. Jiang, Filtering-based accelerated estimation approach for generalized time-varying systems with disturbances and colored noises. IEEE Trans. Circuits Syst. II Express Briefs 70(1), 206–210 (2023)
50.
Zurück zum Zitat Y. Ji, X.K. Jiang, L.J. Wan, Hierarchical least squares parameter estimation algorithm for two-input Hammerstein finite impulse response systems. J. Frankl. Inst. 357(8), 5019–5032 (2020)MathSciNet Y. Ji, X.K. Jiang, L.J. Wan, Hierarchical least squares parameter estimation algorithm for two-input Hammerstein finite impulse response systems. J. Frankl. Inst. 357(8), 5019–5032 (2020)MathSciNet
51.
Zurück zum Zitat Y. Ji, Z. Kang, Three-stage forgetting factor stochastic gradient parameter estimation methods for a class of nonlinear systems. Int. J. Robust Nonlinear Control 31(3), 971–987 (2021)MathSciNet Y. Ji, Z. Kang, Three-stage forgetting factor stochastic gradient parameter estimation methods for a class of nonlinear systems. Int. J. Robust Nonlinear Control 31(3), 971–987 (2021)MathSciNet
52.
Zurück zum Zitat Y. Ji, Z. Kang, X.M. Liu, The data filtering based multiple-stage Levenberg-Marquardt algorithm for Hammerstein nonlinear systems. Int. J. Robust Nonlinear Control 31(15), 7007–7025 (2021)MathSciNet Y. Ji, Z. Kang, X.M. Liu, The data filtering based multiple-stage Levenberg-Marquardt algorithm for Hammerstein nonlinear systems. Int. J. Robust Nonlinear Control 31(15), 7007–7025 (2021)MathSciNet
53.
Zurück zum Zitat Y. Ji, Z. Kang, C. Zhang, Two-stage gradient-based recursive estimation for nonlinear models by using the data filtering. Int. J. Control Autom. Syst. 19(8), 2706–2715 (2021) Y. Ji, Z. Kang, C. Zhang, Two-stage gradient-based recursive estimation for nonlinear models by using the data filtering. Int. J. Control Autom. Syst. 19(8), 2706–2715 (2021)
54.
Zurück zum Zitat Y. Ji, Z. Kang, X. Zhang, L. Xu, Model recovery for multi-input signal-output nonlinear systems based on the compressed sensing recovery theory. J. Frankl. Inst. 359(5), 2317–2339 (2022)MathSciNet Y. Ji, Z. Kang, X. Zhang, L. Xu, Model recovery for multi-input signal-output nonlinear systems based on the compressed sensing recovery theory. J. Frankl. Inst. 359(5), 2317–2339 (2022)MathSciNet
55.
Zurück zum Zitat Y. Ji, J. Liu, H.B. Liu, An identification algorithm of generalized time-varying systems based on the Taylor series expansion and applied to a pH process. J. Process Control 128, 103007 (2023) Y. Ji, J. Liu, H.B. Liu, An identification algorithm of generalized time-varying systems based on the Taylor series expansion and applied to a pH process. J. Process Control 128, 103007 (2023)
56.
Zurück zum Zitat Y. Ji, C. Zhang, Z. Kang, T. Yu, Parameter estimation for block-oriented nonlinear systems using the key term separation. Int. J. Robust Nonlinear Control 30(9), 3727–3752 (2020)MathSciNet Y. Ji, C. Zhang, Z. Kang, T. Yu, Parameter estimation for block-oriented nonlinear systems using the key term separation. Int. J. Robust Nonlinear Control 30(9), 3727–3752 (2020)MathSciNet
57.
Zurück zum Zitat A.N. Jiang, Y. Ji, L.J. Wan, Iterative parameter identification algorithms for the generalized time-varying system with a measurable disturbance vector. Int. J. Robust Nonlinear Control 32(6), 3527–3548 (2020) A.N. Jiang, Y. Ji, L.J. Wan, Iterative parameter identification algorithms for the generalized time-varying system with a measurable disturbance vector. Int. J. Robust Nonlinear Control 32(6), 3527–3548 (2020)
58.
Zurück zum Zitat S. Koga, M. Krstic, State estimation of the Stefan PDE: A tutorial on design and applications topolar ice and batteries. Annu. Rev. Control. 53, 199–223 (2022)MathSciNet S. Koga, M. Krstic, State estimation of the Stefan PDE: A tutorial on design and applications topolar ice and batteries. Annu. Rev. Control. 53, 199–223 (2022)MathSciNet
59.
Zurück zum Zitat J.M. Li, A novel nonlinear optimization method for fitting a noisy Gaussian activation function. Int. J. Adapt. Control Signal Process. 36(3), 690–707 (2022) J.M. Li, A novel nonlinear optimization method for fitting a noisy Gaussian activation function. Int. J. Adapt. Control Signal Process. 36(3), 690–707 (2022)
60.
Zurück zum Zitat M. Li, X. Liu, The least squares based iterative algorithms for parameter estimation of a bilinear system with autoregressive noise using the data filtering technique. Signal Process. 147, 23–34 (2018) M. Li, X. Liu, The least squares based iterative algorithms for parameter estimation of a bilinear system with autoregressive noise using the data filtering technique. Signal Process. 147, 23–34 (2018)
61.
Zurück zum Zitat M.H. Li, X.M. Liu, Maximum likelihood hierarchical least squares-based iterative identification for dual-rate stochastic systems. Int. J. Adapt. Control Signal Process. 35(2), 240–261 (2021)MathSciNet M.H. Li, X.M. Liu, Maximum likelihood hierarchical least squares-based iterative identification for dual-rate stochastic systems. Int. J. Adapt. Control Signal Process. 35(2), 240–261 (2021)MathSciNet
62.
Zurück zum Zitat M.H. Li, X.M. Liu, Iterative identification methods for a class of bilinear systems by using the particle filtering technique. Int. J. Adapt. Control Signal Process. 35(10), 2056–2074 (2021)MathSciNet M.H. Li, X.M. Liu, Iterative identification methods for a class of bilinear systems by using the particle filtering technique. Int. J. Adapt. Control Signal Process. 35(10), 2056–2074 (2021)MathSciNet
63.
Zurück zum Zitat M.H. Li, X.M. Liu, Particle filtering-based iterative identification methods for a class of nonlinear systems with interval-varying measurements. Int. J. Control Autom. Syst. 20(7), 2239–2248 (2022) M.H. Li, X.M. Liu, Particle filtering-based iterative identification methods for a class of nonlinear systems with interval-varying measurements. Int. J. Control Autom. Syst. 20(7), 2239–2248 (2022)
64.
Zurück zum Zitat M.H. Li, X.M. Liu, The filtering-based maximum likelihood iterative estimation algorithms for a special class of nonlinear systems with autoregressive moving average noise using the hierarchical identification principle. Int. J. Adapt. Control Signal Process. 33(7), 1189–1211 (2019)MathSciNet M.H. Li, X.M. Liu, The filtering-based maximum likelihood iterative estimation algorithms for a special class of nonlinear systems with autoregressive moving average noise using the hierarchical identification principle. Int. J. Adapt. Control Signal Process. 33(7), 1189–1211 (2019)MathSciNet
65.
Zurück zum Zitat L.H. Li, G.C. Yang, Y. Li et al., Abnormal sitting posture recognition based on multi-scale spatiotemporal features of skeleton graph. Eng. Appl. Artif. Intell. 123, 106374 (2023) L.H. Li, G.C. Yang, Y. Li et al., Abnormal sitting posture recognition based on multi-scale spatiotemporal features of skeleton graph. Eng. Appl. Artif. Intell. 123, 106374 (2023)
66.
Zurück zum Zitat Y. Li, G. Yang, Z. Su, Y. Wang, Human activity recognition based on multienvironment sensor data. Inf. Fusion 91, 47–63 (2023) Y. Li, G. Yang, Z. Su, Y. Wang, Human activity recognition based on multienvironment sensor data. Inf. Fusion 91, 47–63 (2023)
67.
Zurück zum Zitat L. Liao, X. Hu, H. Chen, Z. Wang, T. Wu, Quantitative diagnosis of micro-short circuit for lithium-ion batteries considering aging based on incremental capacity curve. J. Energy Storage 79, 110240 (2024) L. Liao, X. Hu, H. Chen, Z. Wang, T. Wu, Quantitative diagnosis of micro-short circuit for lithium-ion batteries considering aging based on incremental capacity curve. J. Energy Storage 79, 110240 (2024)
68.
Zurück zum Zitat L. Liao, X. Hu, H. Li, S. Sun, J. Jiang, Design of an improved modular multilevel converter reconfigurable equalization scheme based on difference of voltage variation. J. Electrochem. Energy Convers. Storage 21(3), 031010 (2024) L. Liao, X. Hu, H. Li, S. Sun, J. Jiang, Design of an improved modular multilevel converter reconfigurable equalization scheme based on difference of voltage variation. J. Electrochem. Energy Convers. Storage 21(3), 031010 (2024)
71.
Zurück zum Zitat Q.Y. Liu, F.Y. Chen, Model transformation based distributed stochastic gradient algorithm for multivariate output-error systems. Int. J. Syst. Sci. 54(7), 1484–1502 (2023)MathSciNet Q.Y. Liu, F.Y. Chen, Model transformation based distributed stochastic gradient algorithm for multivariate output-error systems. Int. J. Syst. Sci. 54(7), 1484–1502 (2023)MathSciNet
72.
Zurück zum Zitat S.Y. Liu, F. Ding, Hierarchical principle-based iterative parameter estimation algorithm for dual-frequency signals. Circuits Syst. Signal Process. 38(7), 3251–3268 (2019) S.Y. Liu, F. Ding, Hierarchical principle-based iterative parameter estimation algorithm for dual-frequency signals. Circuits Syst. Signal Process. 38(7), 3251–3268 (2019)
73.
Zurück zum Zitat X.M. Liu, Y.M. Fan, Maximum likelihood extended gradient-based estimation algorithms for the input nonlinear controlled autoregressive moving average system with variable-gain nonlinearity. Int. J. Robust Nonlinear Control 31(9), 4017–4036 (2021)MathSciNet X.M. Liu, Y.M. Fan, Maximum likelihood extended gradient-based estimation algorithms for the input nonlinear controlled autoregressive moving average system with variable-gain nonlinearity. Int. J. Robust Nonlinear Control 31(9), 4017–4036 (2021)MathSciNet
74.
Zurück zum Zitat W.X. Liu, M.H. Li, Unbiased recursive least squares identification methods for a class of nonlinear systems with irregularly missing data. Int. J. Adapt. Control Signal Process. 37(8), 2247–2275 (2023)MathSciNet W.X. Liu, M.H. Li, Unbiased recursive least squares identification methods for a class of nonlinear systems with irregularly missing data. Int. J. Adapt. Control Signal Process. 37(8), 2247–2275 (2023)MathSciNet
75.
Zurück zum Zitat L.J. Liu, H.B. Liu, Data filtering based maximum likelihood gradient estimation algorithms for a multivariate equation-error system with ARMA noise. J. Frankl. Inst. 357, 5640–5662 (2020)MathSciNet L.J. Liu, H.B. Liu, Data filtering based maximum likelihood gradient estimation algorithms for a multivariate equation-error system with ARMA noise. J. Frankl. Inst. 357, 5640–5662 (2020)MathSciNet
76.
Zurück zum Zitat S.Y. Liu, Y.J. Wang, T. Hayat, Joint iterative state and parameter estimation for bilinear systems with autoregressive noises via the data filtering. ISA Trans. 147, 337–349 (2024) S.Y. Liu, Y.J. Wang, T. Hayat, Joint iterative state and parameter estimation for bilinear systems with autoregressive noises via the data filtering. ISA Trans. 147, 337–349 (2024)
77.
Zurück zum Zitat H.B. Liu, J.W. Wang, Maximum likelihood recursive generalized extended least squares estimation methods for a bilinear-parameter systems with ARMA noise based on the over-parameterization model. Int. J. Control Autom. Syst. 20(8), 2606–2615 (2022) H.B. Liu, J.W. Wang, Maximum likelihood recursive generalized extended least squares estimation methods for a bilinear-parameter systems with ARMA noise based on the over-parameterization model. Int. J. Control Autom. Syst. 20(8), 2606–2615 (2022)
78.
Zurück zum Zitat H.B. Liu, J.W. Wang, Hierarchical maximum likelihood generalized extended stochastic gradient algorithms for bilinear-in-parameter systems. Optimal Control Appl. Methods 43(2), 402–417 (2022)MathSciNet H.B. Liu, J.W. Wang, Hierarchical maximum likelihood generalized extended stochastic gradient algorithms for bilinear-in-parameter systems. Optimal Control Appl. Methods 43(2), 402–417 (2022)MathSciNet
79.
Zurück zum Zitat L.J. Liu, H.F. Xia, Auxiliary model-based maximum likelihood gradient iterative identification for feedback nonlinear systems. Optimal Control Appl. Methods 45 (2024) L.J. Liu, H.F. Xia, Auxiliary model-based maximum likelihood gradient iterative identification for feedback nonlinear systems. Optimal Control Appl. Methods 45 (2024)
80.
Zurück zum Zitat S.Y. Liu, X. Zhang, Expectation-maximization algorithm for bilinear systems by using the Rauch-Tung-Striebel smoother. Automatica 142, 110365 (2022)MathSciNet S.Y. Liu, X. Zhang, Expectation-maximization algorithm for bilinear systems by using the Rauch-Tung-Striebel smoother. Automatica 142, 110365 (2022)MathSciNet
81.
Zurück zum Zitat H. Ma, J. Pan, W. Ding, Partially-coupled least squares based iterative parameter estimation for multi-variable output-error-like autoregressive moving average systems. IET Control Theory Appl. 13(18), 3040–3051 (2019)MathSciNet H. Ma, J. Pan, W. Ding, Partially-coupled least squares based iterative parameter estimation for multi-variable output-error-like autoregressive moving average systems. IET Control Theory Appl. 13(18), 3040–3051 (2019)MathSciNet
82.
Zurück zum Zitat Y.W. Mao, C. Xu, J. Chen, Y. Pu, Q.Y. Hu, Auxiliary model-based iterative estimation algorithms for nonlinear systems using the covariance matrix adaptation strategy. Circuits Syst. Signal Process. 41(12), 6750–6773 (2022) Y.W. Mao, C. Xu, J. Chen, Y. Pu, Q.Y. Hu, Auxiliary model-based iterative estimation algorithms for nonlinear systems using the covariance matrix adaptation strategy. Circuits Syst. Signal Process. 41(12), 6750–6773 (2022)
83.
Zurück zum Zitat M. Mejari, D. Piga, A. Bemporad, A bias-correction method for closed-loop identification of linear parameter-varying systems. Automatica 87, 128–141 (2018)MathSciNet M. Mejari, D. Piga, A. Bemporad, A bias-correction method for closed-loop identification of linear parameter-varying systems. Automatica 87, 128–141 (2018)MathSciNet
84.
Zurück zum Zitat G.Q. Miao, E.F. Yang, Iterative parameter identification algorithms for transformed dynamic rational fraction input-output systems. J. Comput. Appl. Math. 434, 115297 (2023)MathSciNet G.Q. Miao, E.F. Yang, Iterative parameter identification algorithms for transformed dynamic rational fraction input-output systems. J. Comput. Appl. Math. 434, 115297 (2023)MathSciNet
85.
Zurück zum Zitat H.I. Nurdin, M. Guta, Parameter estimation and system identification for continuously-observed quantum systems. Annu. Rev. Control 54, 295–304 (2022)MathSciNet H.I. Nurdin, M. Guta, Parameter estimation and system identification for continuously-observed quantum systems. Annu. Rev. Control 54, 295–304 (2022)MathSciNet
86.
Zurück zum Zitat J. Pan, Q. Chen, J. Xiong, G. Chen, A novel quadruple-boost nine-level switched capacitor inverter. J. Electr. Eng. Technol. 18(1), 467–480 (2023) J. Pan, Q. Chen, J. Xiong, G. Chen, A novel quadruple-boost nine-level switched capacitor inverter. J. Electr. Eng. Technol. 18(1), 467–480 (2023)
87.
Zurück zum Zitat J. Pan, X. Jiang, X.K. Wan, W. Ding, A filtering based multi-innovation extended stochastic gradient algorithm for multivariable control systems. Int. J. Control Autom. Syst. 15(3), 1189–1197 (2017) J. Pan, X. Jiang, X.K. Wan, W. Ding, A filtering based multi-innovation extended stochastic gradient algorithm for multivariable control systems. Int. J. Control Autom. Syst. 15(3), 1189–1197 (2017)
88.
Zurück zum Zitat J. Pan, W. Li, H.P. Zhang, Control algorithms of magnetic suspension systems based on the improved double exponential reaching law of sliding mode control. Int. J. Control Autom. Syst. 16(6), 2878–2887 (2018) J. Pan, W. Li, H.P. Zhang, Control algorithms of magnetic suspension systems based on the improved double exponential reaching law of sliding mode control. Int. J. Control Autom. Syst. 16(6), 2878–2887 (2018)
89.
Zurück zum Zitat J. Pan, Y.Q. Liu, J. Shu, Gradient-based parameter estimation for an exponential nonlinear autoregressive time-series model by using the multi-innovation. Int. J. Control Autom. Syst. 21(1), 140–150 (2023) J. Pan, Y.Q. Liu, J. Shu, Gradient-based parameter estimation for an exponential nonlinear autoregressive time-series model by using the multi-innovation. Int. J. Control Autom. Syst. 21(1), 140–150 (2023)
90.
Zurück zum Zitat J. Pan, S.D. Liu, J. Shu, X.K. Wan, Hierarchical recursive least squares estimation algorithm for second-order Volterra nonlinear systems. Int. J. Control Autom. Syst. 20(12), 3940–3950 (2022) J. Pan, S.D. Liu, J. Shu, X.K. Wan, Hierarchical recursive least squares estimation algorithm for second-order Volterra nonlinear systems. Int. J. Control Autom. Syst. 20(12), 3940–3950 (2022)
91.
Zurück zum Zitat J. Pan, H. Ma, X. Zhang et al., Recursive coupled projection algorithms for multivariable output-error-like systems with coloured noises. IET Signal Process. 14(7), 455–466 (2020) J. Pan, H. Ma, X. Zhang et al., Recursive coupled projection algorithms for multivariable output-error-like systems with coloured noises. IET Signal Process. 14(7), 455–466 (2020)
92.
Zurück zum Zitat J. Pan, B. Shao, J.X. Xiong, Q. Zhang, Attitude control of quadrotor UAVs based on adaptive sliding mode. Int. J. Control Autom. Syst. 21(8), 2698–2707 (2023) J. Pan, B. Shao, J.X. Xiong, Q. Zhang, Attitude control of quadrotor UAVs based on adaptive sliding mode. Int. J. Control Autom. Syst. 21(8), 2698–2707 (2023)
93.
Zurück zum Zitat J. Pan, H. Zhang, H. Guo, S. Liu, Y. Liu, Multivariable CAR-like system identification with multi-innovation gradient and least squares algorithms. Int. J. Control Autom. Syst. 21(5), 1455–1464 (2023) J. Pan, H. Zhang, H. Guo, S. Liu, Y. Liu, Multivariable CAR-like system identification with multi-innovation gradient and least squares algorithms. Int. J. Control Autom. Syst. 21(5), 1455–1464 (2023)
94.
Zurück zum Zitat I.R. Petersen, D. Dong, Special section on estimation and control of quantum systems. Annu. Rev. Control. 54, 241–242 (2022)MathSciNet I.R. Petersen, D. Dong, Special section on estimation and control of quantum systems. Annu. Rev. Control. 54, 241–242 (2022)MathSciNet
95.
Zurück zum Zitat D. Piga, V. Breschi, A. Bemporad, Estimation of jump Box-Jenkins models. Automatica 120(7), 109126 (2020)MathSciNet D. Piga, V. Breschi, A. Bemporad, Estimation of jump Box-Jenkins models. Automatica 120(7), 109126 (2020)MathSciNet
96.
Zurück zum Zitat R.M.S. Pimenta, N.N. Siqueira, M.R. Petraglia, D.B. Haddad, Transient analysis of the bias-compensated LMS algorithm. J. Commun. Inf. Syst. 36(1), 114–118 (2021) R.M.S. Pimenta, N.N. Siqueira, M.R. Petraglia, D.B. Haddad, Transient analysis of the bias-compensated LMS algorithm. J. Commun. Inf. Syst. 36(1), 114–118 (2021)
97.
Zurück zum Zitat A. Saviolo, G. Loianno, Learning quadrotor dynamics for precise, safe, and agile flight control. Annu. Rev. Control. 55, 45–60 (2023)MathSciNet A. Saviolo, G. Loianno, Learning quadrotor dynamics for precise, safe, and agile flight control. Annu. Rev. Control. 55, 45–60 (2023)MathSciNet
98.
Zurück zum Zitat Z.W. Shi, Y. Wang, Z.C. Ji, Bias compensation based partially coupled recursive least squares identification algorithm with forgetting factors for MIMO systems: application to PMSMs. J. Frankl. Inst. 353(13), 3057–3077 (2016)MathSciNet Z.W. Shi, Y. Wang, Z.C. Ji, Bias compensation based partially coupled recursive least squares identification algorithm with forgetting factors for MIMO systems: application to PMSMs. J. Frankl. Inst. 353(13), 3057–3077 (2016)MathSciNet
99.
Zurück zum Zitat J. Shu, S. Wang, S. Yu, J. Zhang, CFSA-Net: efficient large-scale point cloud semantic segmentation based on cross-fusion self-attention. CMC-Comput. Mat. Contin. 77(3), 2677–2697 (2023) J. Shu, S. Wang, S. Yu, J. Zhang, CFSA-Net: efficient large-scale point cloud semantic segmentation based on cross-fusion self-attention. CMC-Comput. Mat. Contin. 77(3), 2677–2697 (2023)
100.
Zurück zum Zitat T. Söderström, M. Hong, W.X. Zheng, Convergence properties of bias-eliminating algorithms for errors-in-variables identification. Int. J. Adapt. Control Signal Process. 19(9), 703–722 (2005)MathSciNet T. Söderström, M. Hong, W.X. Zheng, Convergence properties of bias-eliminating algorithms for errors-in-variables identification. Int. J. Adapt. Control Signal Process. 19(9), 703–722 (2005)MathSciNet
101.
Zurück zum Zitat P. Stoica, T. Söderström, Bias correction in least-squares identification. Int. J. Control 35(3), 449–457 (1982)MathSciNet P. Stoica, T. Söderström, Bias correction in least-squares identification. Int. J. Control 35(3), 449–457 (1982)MathSciNet
102.
Zurück zum Zitat S. Su, J. She, K. Li et al., A nonlinear safety equilibrium spacing based model predictive control for virtually coupled train set over gradient terrains. IEEE Trans. Transp. Electrif. 8(2), 2810–2824 (2022) S. Su, J. She, K. Li et al., A nonlinear safety equilibrium spacing based model predictive control for virtually coupled train set over gradient terrains. IEEE Trans. Transp. Electrif. 8(2), 2810–2824 (2022)
103.
Zurück zum Zitat S. Su, T. Tang, J. Xun et al., Design of running grades for energy-efficient train regulation: a case study for Beijing Yizhuang line. IEEE Intell. Transp. Syst. Mag. 13(2), 189–200 (2021) S. Su, T. Tang, J. Xun et al., Design of running grades for energy-efficient train regulation: a case study for Beijing Yizhuang line. IEEE Intell. Transp. Syst. Mag. 13(2), 189–200 (2021)
104.
Zurück zum Zitat S. Su, X. Wang, Y. Cao, J.T. Yin, An energy-efficient train operation approach by integrating the metro timetabling and eco-driving. IEEE Trans. Intell. Transp. Syst. 21(10), 4252–4268 (2020) S. Su, X. Wang, Y. Cao, J.T. Yin, An energy-efficient train operation approach by integrating the metro timetabling and eco-driving. IEEE Trans. Intell. Transp. Syst. 21(10), 4252–4268 (2020)
105.
Zurück zum Zitat S. Su, X. Wang, T. Tang, et al., Energy-efficient operation by cooperative control among trains: a multi-agent reinforcement learning approach. Control Eng. Pract. 116, Article Number: 104901 (2021) S. Su, X. Wang, T. Tang, et al., Energy-efficient operation by cooperative control among trains: a multi-agent reinforcement learning approach. Control Eng. Pract. 116, Article Number: 104901 (2021)
106.
Zurück zum Zitat S. Su, Q. Zhu, J. Liu et al., Eco-driving of trains with a data-driven iterative learning approach. IEEE Trans. Ind. Inf. 19(7), 7885–7893 (2023) S. Su, Q. Zhu, J. Liu et al., Eco-driving of trains with a data-driven iterative learning approach. IEEE Trans. Ind. Inf. 19(7), 7885–7893 (2023)
107.
Zurück zum Zitat Y.K. Sun, Y. Cao, P. Li, Contactless fault diagnosis for railway point machines based on multi-scale fractional wavelet packet energy entropy and synchronous optimization strategy. IEEE Trans. Veh. Technol. 71(6), 5906–5914 (2022) Y.K. Sun, Y. Cao, P. Li, Contactless fault diagnosis for railway point machines based on multi-scale fractional wavelet packet energy entropy and synchronous optimization strategy. IEEE Trans. Veh. Technol. 71(6), 5906–5914 (2022)
108.
Zurück zum Zitat Y.K. Sun, Y. Cao, L.C. Ma, A fault diagnosis method for train plug doors via sound signals. IEEE Intell. Transp. Syst. Mag. 13(3), 107–117 (2021) Y.K. Sun, Y. Cao, L.C. Ma, A fault diagnosis method for train plug doors via sound signals. IEEE Intell. Transp. Syst. Mag. 13(3), 107–117 (2021)
109.
Zurück zum Zitat Y.K. Sun, Y. Cao, G. Xie, T. Wen, Sound based fault diagnosis for RPMs based on multi-scale fractional permutation entropy and two-scale algorithm. IEEE Trans. Veh. Technol. 70(11), 11184–11192 (2021) Y.K. Sun, Y. Cao, G. Xie, T. Wen, Sound based fault diagnosis for RPMs based on multi-scale fractional permutation entropy and two-scale algorithm. IEEE Trans. Veh. Technol. 70(11), 11184–11192 (2021)
110.
Zurück zum Zitat S.Y. Sun, L. Xu, Filtered multi-innovation-based iterative identification methods for multivariate equation-error ARMA systems. Int. J. Adapt. Control Signal Process. 37(3), 836–855 (2023)MathSciNet S.Y. Sun, L. Xu, Filtered multi-innovation-based iterative identification methods for multivariate equation-error ARMA systems. Int. J. Adapt. Control Signal Process. 37(3), 836–855 (2023)MathSciNet
111.
Zurück zum Zitat S.Y. Sun, X. Wang, Hierarchical iterative identification algorithms for a nonlinear system with dead-zone and saturation nonlinearity based on the auxiliary model. Int. J. Adapt. Control Signal Process. 37(7), 1866–1892 (2023) S.Y. Sun, X. Wang, Hierarchical iterative identification algorithms for a nonlinear system with dead-zone and saturation nonlinearity based on the auxiliary model. Int. J. Adapt. Control Signal Process. 37(7), 1866–1892 (2023)
112.
Zurück zum Zitat L.J. Wan, F. Ding, Decomposition- and gradient-based iterative identification algorithms for multivariable systems using the multi-innovation theory. Circuits Syst. Signal Process. 38(7), 2971–2991 (2019) L.J. Wan, F. Ding, Decomposition- and gradient-based iterative identification algorithms for multivariable systems using the multi-innovation theory. Circuits Syst. Signal Process. 38(7), 2971–2991 (2019)
113.
Zurück zum Zitat D. Wang, Y. Chu, Auxiliary model-based RELS and MI-ELS algorithm for Hammerstein OEMA systems. Comput. Math. Appl. 59(9), 3092–3098 (2010)MathSciNet D. Wang, Y. Chu, Auxiliary model-based RELS and MI-ELS algorithm for Hammerstein OEMA systems. Comput. Math. Appl. 59(9), 3092–3098 (2010)MathSciNet
114.
Zurück zum Zitat X.H. Wang, F. Ding, Modified particle filtering-based robust estimation for a networked control system corrupted by impulsive noise. Int. J. Robust Nonlinear Control 32(2), 830–850 (2022)MathSciNet X.H. Wang, F. Ding, Modified particle filtering-based robust estimation for a networked control system corrupted by impulsive noise. Int. J. Robust Nonlinear Control 32(2), 830–850 (2022)MathSciNet
115.
Zurück zum Zitat Y. Wang, F. Ding, The filtering based iterative identification for multivariable systems. IET Control Theory Appl. 10(8), 894–902 (2016)MathSciNet Y. Wang, F. Ding, The filtering based iterative identification for multivariable systems. IET Control Theory Appl. 10(8), 894–902 (2016)MathSciNet
116.
Zurück zum Zitat Y. Wang, F. Ding, Novel data filtering-based parameter identification for multiple-input multiple-output systems using the auxiliary model. Automatica 71, 308–313 (2016)MathSciNet Y. Wang, F. Ding, Novel data filtering-based parameter identification for multiple-input multiple-output systems using the auxiliary model. Automatica 71, 308–313 (2016)MathSciNet
117.
Zurück zum Zitat Y.J. Wang, F. Ding, Recursive parameter estimation algorithm for multivariate output-error systems. J. Frankl. Inst. 355(12), 5163–5181 (2018)MathSciNet Y.J. Wang, F. Ding, Recursive parameter estimation algorithm for multivariate output-error systems. J. Frankl. Inst. 355(12), 5163–5181 (2018)MathSciNet
118.
Zurück zum Zitat H.J. Wang, G.Y. Ke, F.Y. Hu, J. Pan, Q.F. Su, G.L. Dong, G. Chen, Pseudo and true singularly degenerate heteroclinic cycles of a new 3D cubic Lorenz-like system. Results Phys. 56, 107243 (2024) H.J. Wang, G.Y. Ke, F.Y. Hu, J. Pan, Q.F. Su, G.L. Dong, G. Chen, Pseudo and true singularly degenerate heteroclinic cycles of a new 3D cubic Lorenz-like system. Results Phys. 56, 107243 (2024)
119.
Zurück zum Zitat X.Y. Wang, J.X. Ma, W.L. Xiong, Expectation-maximization algorithm for bilinear state-space models with time-varying delays under non-Gaussian noise. Int. J. Adapt. Control Signal Process. 37(10), 2706–2724 (2023)MathSciNet X.Y. Wang, J.X. Ma, W.L. Xiong, Expectation-maximization algorithm for bilinear state-space models with time-varying delays under non-Gaussian noise. Int. J. Adapt. Control Signal Process. 37(10), 2706–2724 (2023)MathSciNet
120.
Zurück zum Zitat J.W. Wang, Y. Ji, X. Zhang, L. Xu, Two-stage gradient-based iterative algorithms for the fractional-order nonlinear systems by using the hierarchical identification principle. Int. J. Adapt. Control Signal Process. 36(7), 1778–1796 (2022)MathSciNet J.W. Wang, Y. Ji, X. Zhang, L. Xu, Two-stage gradient-based iterative algorithms for the fractional-order nonlinear systems by using the hierarchical identification principle. Int. J. Adapt. Control Signal Process. 36(7), 1778–1796 (2022)MathSciNet
121.
Zurück zum Zitat X. Wang, S. Su, Y. Cao, X.L. Wang, Robust control for dynamic train regulation in fully automatic operation system under uncertain wireless transmissions. IEEE Trans. Intell. Transp. Syst. 23(11), 20721–20734 (2022) X. Wang, S. Su, Y. Cao, X.L. Wang, Robust control for dynamic train regulation in fully automatic operation system under uncertain wireless transmissions. IEEE Trans. Intell. Transp. Syst. 23(11), 20721–20734 (2022)
122.
Zurück zum Zitat Y. Wang, G. Yang, Arrhythmia classification algorithm based on multi-head self-attention mechanism. Biomed. Signal Process. Control 79, 104206 (2023) Y. Wang, G. Yang, Arrhythmia classification algorithm based on multi-head self-attention mechanism. Biomed. Signal Process. Control 79, 104206 (2023)
123.
Zurück zum Zitat A.G. Wu, S. Chen, D.L. Jia, Bias-compensation-based least-squares estimation with a forgetting factor for output error models with white noise. Int. J. Syst. 47(5–8), 1700–1709 (2016)MathSciNet A.G. Wu, S. Chen, D.L. Jia, Bias-compensation-based least-squares estimation with a forgetting factor for output error models with white noise. Int. J. Syst. 47(5–8), 1700–1709 (2016)MathSciNet
124.
Zurück zum Zitat A.G. Wu, Y.Y. Qian, W.J. Wu, Bias compensation-based recursive least-squares estimation with forgetting factors for output error moving average systems. IET Signal Process. 8(5), 483–494 (2013) A.G. Wu, Y.Y. Qian, W.J. Wu, Bias compensation-based recursive least-squares estimation with forgetting factors for output error moving average systems. IET Signal Process. 8(5), 483–494 (2013)
125.
Zurück zum Zitat C. Wei, Overall recursive least squares and overall stochastic gradient algorithms and their convergence for feedback nonlinear controlled autoregressive systems. Int. J. Robust Nonlinear Control 32(9), 5534–5554 (2022)MathSciNet C. Wei, Overall recursive least squares and overall stochastic gradient algorithms and their convergence for feedback nonlinear controlled autoregressive systems. Int. J. Robust Nonlinear Control 32(9), 5534–5554 (2022)MathSciNet
126.
Zurück zum Zitat H.M. Xing, E.F. Yang, Hierarchical recursive least squares parameter estimation methods for multiple-input multiple-output systems by using the auxiliary models. Int. J. Adapt. Control Signal Process. 37(11), 2983–3007 (2023)MathSciNet H.M. Xing, E.F. Yang, Hierarchical recursive least squares parameter estimation methods for multiple-input multiple-output systems by using the auxiliary models. Int. J. Adapt. Control Signal Process. 37(11), 2983–3007 (2023)MathSciNet
127.
Zurück zum Zitat H.M. Xing, E.F. Yang, Highly-efficient filtered hierarchical identification algorithms for multiple-input multiple-output systems with colored noises. Syst. Control Lett. 186, 105762 (2024)MathSciNet H.M. Xing, E.F. Yang, Highly-efficient filtered hierarchical identification algorithms for multiple-input multiple-output systems with colored noises. Syst. Control Lett. 186, 105762 (2024)MathSciNet
128.
Zurück zum Zitat J.X. Xiong, J. Pan, G.Y. Chen, Sliding mode dual-channel disturbance rejection attitude control for a quadrotor. IEEE Trans. Ind. Electron. 69(10), 10489–10499 (2022) J.X. Xiong, J. Pan, G.Y. Chen, Sliding mode dual-channel disturbance rejection attitude control for a quadrotor. IEEE Trans. Ind. Electron. 69(10), 10489–10499 (2022)
129.
Zurück zum Zitat L. Xu, Separable multi-innovation Newton iterative modeling algorithm for multi-frequency signals based on the sliding measurement window. Circuits Syst. Signal Process. 41(2), 805–830 (2022) L. Xu, Separable multi-innovation Newton iterative modeling algorithm for multi-frequency signals based on the sliding measurement window. Circuits Syst. Signal Process. 41(2), 805–830 (2022)
130.
Zurück zum Zitat L. Xu, Parameter estimation for nonlinear functions related to system responses. Int. J. Control Autom. Syst. 21(6), 1780–1792 (2023) L. Xu, Parameter estimation for nonlinear functions related to system responses. Int. J. Control Autom. Syst. 21(6), 1780–1792 (2023)
131.
Zurück zum Zitat L. Xu, Separable Newton recursive estimation method through system responses based on dynamically discrete measurements with increasing data length. Int. J. Control Autom. Syst. 20(2), 432–443 (2022) L. Xu, Separable Newton recursive estimation method through system responses based on dynamically discrete measurements with increasing data length. Int. J. Control Autom. Syst. 20(2), 432–443 (2022)
132.
Zurück zum Zitat H. Xu, Joint parameter and time-delay estimation for a class of nonlinear time-series models. IEEE Signal Process. Lett. 29, 947–951 (2022) H. Xu, Joint parameter and time-delay estimation for a class of nonlinear time-series models. IEEE Signal Process. Lett. 29, 947–951 (2022)
133.
Zurück zum Zitat L. Xu, Separable synthesis estimation methods and convergence analysis for multivariable systems. J. Comput. Appl. Math. 427, 115104 (2023)MathSciNet L. Xu, Separable synthesis estimation methods and convergence analysis for multivariable systems. J. Comput. Appl. Math. 427, 115104 (2023)MathSciNet
134.
Zurück zum Zitat L. Xu, Decomposition and composition modeling algorithms for control systems with colored noises. Int. J. Adapt. Control Signal Process. 38(1), 255–278 (2024)MathSciNet L. Xu, Decomposition and composition modeling algorithms for control systems with colored noises. Int. J. Adapt. Control Signal Process. 38(1), 255–278 (2024)MathSciNet
136.
Zurück zum Zitat L. Xu, Q.M. Zhu, Novel parameter estimation method for the systems with colored noises by using the filtering identification idea. Syst. Control Lett. 186, 105774 (2024)MathSciNet L. Xu, Q.M. Zhu, Novel parameter estimation method for the systems with colored noises by using the filtering identification idea. Syst. Control Lett. 186, 105774 (2024)MathSciNet
137.
Zurück zum Zitat L. Xu, Q.M. Zhu, Separable synchronous multi-innovation gradient based iterative signal modeling from on-line measurements. IEEE Trans. Instrum. Meas. 71, 6501313 (2022) L. Xu, Q.M. Zhu, Separable synchronous multi-innovation gradient based iterative signal modeling from on-line measurements. IEEE Trans. Instrum. Meas. 71, 6501313 (2022)
138.
Zurück zum Zitat C. Xu, Y. Qin, H. Su, Observer-based dynamic event-triggered bipartite consensus of discrete-time multi-agent systems. IEEE Trans. Circuits Syst. II Express Briefs 70(3), 1054–1058 (2023) C. Xu, Y. Qin, H. Su, Observer-based dynamic event-triggered bipartite consensus of discrete-time multi-agent systems. IEEE Trans. Circuits Syst. II Express Briefs 70(3), 1054–1058 (2023)
139.
Zurück zum Zitat C. Xu, H. Xu, Z.H. Guan, Y. Ge, Observer-based dynamic event-triggered semi-global bipartite consensus of linear multi-agent systems with input saturation. IEEE Trans. Cybern. 53(5), 3139–3152 (2023) C. Xu, H. Xu, Z.H. Guan, Y. Ge, Observer-based dynamic event-triggered semi-global bipartite consensus of linear multi-agent systems with input saturation. IEEE Trans. Cybern. 53(5), 3139–3152 (2023)
140.
Zurück zum Zitat C.J. Xu, W. Zeng, C. Liu, H.C. Yan, Event-triggered semi-global output consensus of discrete-time multi-agent systems with input saturation and external disturbances. IEEE Trans. Circuits Syst. II Express Briefs 70(12), 4469–4473 (2023) C.J. Xu, W. Zeng, C. Liu, H.C. Yan, Event-triggered semi-global output consensus of discrete-time multi-agent systems with input saturation and external disturbances. IEEE Trans. Circuits Syst. II Express Briefs 70(12), 4469–4473 (2023)
141.
Zurück zum Zitat D. Yang, F. Ding, Multi-innovation gradient-based iterative identification methods for feedback nonlinear systems by using the decomposition technique. Int. J. Robust Nonlinear Control 33(13), 7755–7773 (2023)MathSciNet D. Yang, F. Ding, Multi-innovation gradient-based iterative identification methods for feedback nonlinear systems by using the decomposition technique. Int. J. Robust Nonlinear Control 33(13), 7755–7773 (2023)MathSciNet
142.
Zurück zum Zitat D. Yang, Y.J. Liu, Hierarchical gradient-based iterative parameter estimation algorithms for a nonlinear feedback system based on the hierarchical identification principle. Circuits Syst. Signal Process. 43(1), 124–151 (2024) D. Yang, Y.J. Liu, Hierarchical gradient-based iterative parameter estimation algorithms for a nonlinear feedback system based on the hierarchical identification principle. Circuits Syst. Signal Process. 43(1), 124–151 (2024)
143.
Zurück zum Zitat G. Yang, S. Li, L. He, Short-term prediction method of blood glucose based on temporal multi-head attention mechanism for diabetic patients. Biomed. Signal Process. Control 82, 104552 (2023) G. Yang, S. Li, L. He, Short-term prediction method of blood glucose based on temporal multi-head attention mechanism for diabetic patients. Biomed. Signal Process. Control 82, 104552 (2023)
144.
Zurück zum Zitat G. Yang, S. Yang, K. Luo, S. La, L. He, Y. Li, Detection of non-suicidal self-injury based on spatiotemporal features of indoor activities. IET Biometrics 12, 91–101 (2023) G. Yang, S. Yang, K. Luo, S. La, L. He, Y. Li, Detection of non-suicidal self-injury based on spatiotemporal features of indoor activities. IET Biometrics 12, 91–101 (2023)
145.
Zurück zum Zitat J. You, C. Yu, J. Sun, J. Chen, Generalized maximum entropy based identification of graphical ARMA models. Automatica 141, 110319 (2022)MathSciNet J. You, C. Yu, J. Sun, J. Chen, Generalized maximum entropy based identification of graphical ARMA models. Automatica 141, 110319 (2022)MathSciNet
146.
Zurück zum Zitat C. Yu, Y. Li, H. Fang, J. Chen, System identification approach for inverse optimal control of finite-horizon linear quadratic regulators. Automatica 129, 109636 (2021)MathSciNet C. Yu, Y. Li, H. Fang, J. Chen, System identification approach for inverse optimal control of finite-horizon linear quadratic regulators. Automatica 129, 109636 (2021)MathSciNet
147.
Zurück zum Zitat Y. Zhang, Unbiased identification of a class of multi-input single-output systems with correlated disturbances using bias compensation methods. Math. Comput. Modell. 53(9–10), 1810–1819 (2011)MathSciNet Y. Zhang, Unbiased identification of a class of multi-input single-output systems with correlated disturbances using bias compensation methods. Math. Comput. Modell. 53(9–10), 1810–1819 (2011)MathSciNet
148.
Zurück zum Zitat X. Zhang, F. Ding, Hierarchical parameter and state estimation for bilinear systems. Int. J. Syst. Sci. 51(2), 275–290 (2020)MathSciNet X. Zhang, F. Ding, Hierarchical parameter and state estimation for bilinear systems. Int. J. Syst. Sci. 51(2), 275–290 (2020)MathSciNet
149.
Zurück zum Zitat X. Zhang, F. Ding, Optimal adaptive filtering algorithm by using the fractional-order derivative. IEEE Signal Process. Lett. 29, 399–403 (2022) X. Zhang, F. Ding, Optimal adaptive filtering algorithm by using the fractional-order derivative. IEEE Signal Process. Lett. 29, 399–403 (2022)
150.
Zurück zum Zitat X. Zhang, F. Ding, Adaptive parameter estimation for a general dynamical system with unknown states. Int. J. Robust Nonlinear Control 30(4), 1351–1372 (2020)MathSciNet X. Zhang, F. Ding, Adaptive parameter estimation for a general dynamical system with unknown states. Int. J. Robust Nonlinear Control 30(4), 1351–1372 (2020)MathSciNet
151.
Zurück zum Zitat X. Zhang, Q. Han, Sampled-data control systems with non-uniform sampling: A survey ofmethods and trends. Annu. Rev. Control. 55, 70–91 (2023)MathSciNet X. Zhang, Q. Han, Sampled-data control systems with non-uniform sampling: A survey ofmethods and trends. Annu. Rev. Control. 55, 70–91 (2023)MathSciNet
152.
Zurück zum Zitat X. Zhang, L. Xu, Recursive parameter estimation methods and convergence analysis for a special class of nonlinear systems. Int. J. Robust Nonlinear Control 30(4), 1373–1393 (2020)MathSciNet X. Zhang, L. Xu, Recursive parameter estimation methods and convergence analysis for a special class of nonlinear systems. Int. J. Robust Nonlinear Control 30(4), 1373–1393 (2020)MathSciNet
153.
Zurück zum Zitat X. Zhang, E.F. Yang, Highly computationally efficient state filter based on the delta operator. Int. J. Adapt. Control Signal Process. 33(6), 875–889 (2019)MathSciNet X. Zhang, E.F. Yang, Highly computationally efficient state filter based on the delta operator. Int. J. Adapt. Control Signal Process. 33(6), 875–889 (2019)MathSciNet
154.
Zurück zum Zitat X. Zhang, E.F. Yang, State estimation for bilinear systems through minimizing the covariance matrix of the state estimation errors. Int. J. Adapt. Control Signal Process. 33(7), 1157–1173 (2019)MathSciNet X. Zhang, E.F. Yang, State estimation for bilinear systems through minimizing the covariance matrix of the state estimation errors. Int. J. Adapt. Control Signal Process. 33(7), 1157–1173 (2019)MathSciNet
155.
Zurück zum Zitat Y. Zhang, H.Z. Yang, Bias compensation recursive least squares identification for output error systems with colored noises. Acta Autom. Sinica 33(10), 1053–1060 (2007) Y. Zhang, H.Z. Yang, Bias compensation recursive least squares identification for output error systems with colored noises. Acta Autom. Sinica 33(10), 1053–1060 (2007)
156.
Zurück zum Zitat T.Y. Zhang, S.Y. Zhao, X.L. Luan, F. Liu, Bayesian inference for state-space models with student-t mixture distributions. IEEE Trans. Cybern. 53(7), 4435–4445 (2023) T.Y. Zhang, S.Y. Zhao, X.L. Luan, F. Liu, Bayesian inference for state-space models with student-t mixture distributions. IEEE Trans. Cybern. 53(7), 4435–4445 (2023)
157.
Zurück zum Zitat S.Y. Zhao, B. Huang, Trial-and-error or avoiding a guess? Initialization of the Kalman filter. Automatica 121, 109184 (2020)MathSciNet S.Y. Zhao, B. Huang, Trial-and-error or avoiding a guess? Initialization of the Kalman filter. Automatica 121, 109184 (2020)MathSciNet
158.
Zurück zum Zitat S.Y. Zhao, B. Huang, C.H. Zhao, Online probabilistic estimation of sensor faulty signal in industrial processes and its applications. IEEE Trans. Ind. Electron. 68(9), 8858–8862 (2021) S.Y. Zhao, B. Huang, C.H. Zhao, Online probabilistic estimation of sensor faulty signal in industrial processes and its applications. IEEE Trans. Ind. Electron. 68(9), 8858–8862 (2021)
159.
Zurück zum Zitat S.Y. Zhao, K. Li, C. Ahn, B. Huang, F. Liu, Tuning-free Bayesian estimation algorithms for faulty sensor signals in state-space. IEEE Trans. Ind. Electron. 70(1), 921–929 (2023) S.Y. Zhao, K. Li, C. Ahn, B. Huang, F. Liu, Tuning-free Bayesian estimation algorithms for faulty sensor signals in state-space. IEEE Trans. Ind. Electron. 70(1), 921–929 (2023)
160.
Zurück zum Zitat Z.Y. Zhao, S. Setsuo, W. Kiyoshi, Bias-compensating least squares method for identification of continuous-time systems from sampled data. Int. J. Control 53(2), 445–461 (1991)MathSciNet Z.Y. Zhao, S. Setsuo, W. Kiyoshi, Bias-compensating least squares method for identification of continuous-time systems from sampled data. Int. J. Control 53(2), 445–461 (1991)MathSciNet
161.
Zurück zum Zitat S.Y. Zhao, Y.S. Shmaliy, C.K. Ahn, F. Liu, Self-tuning unbiased finite impulse response filtering algorithm for processes with unknown measurement noise covariance. IEEE Trans. Control Syst. Technol. 29(3), 1372–1379 (2021) S.Y. Zhao, Y.S. Shmaliy, C.K. Ahn, F. Liu, Self-tuning unbiased finite impulse response filtering algorithm for processes with unknown measurement noise covariance. IEEE Trans. Control Syst. Technol. 29(3), 1372–1379 (2021)
162.
Zurück zum Zitat S.Y. Zhao, Y.S. Shmaliy, C.K. Ahn, L.J. Luo, An improved iterative FIR state estimator and its applications. IEEE Trans. Ind. Inf. 16(2), 1003–1012 (2020) S.Y. Zhao, Y.S. Shmaliy, C.K. Ahn, L.J. Luo, An improved iterative FIR state estimator and its applications. IEEE Trans. Ind. Inf. 16(2), 1003–1012 (2020)
163.
Zurück zum Zitat S.Y. Zhao, Y.S. Shmaliy, C.K. Ahn, C.H. Zhao, Probabilistic monitoring of correlated sensors for nonlinear processes in state space. IEEE Trans. Ind. Electron. 67(3), 2294–2303 (2020) S.Y. Zhao, Y.S. Shmaliy, C.K. Ahn, C.H. Zhao, Probabilistic monitoring of correlated sensors for nonlinear processes in state space. IEEE Trans. Ind. Electron. 67(3), 2294–2303 (2020)
164.
Zurück zum Zitat S.Y. Zhao, Y.S. Shmaliy, J.A. Andrade-Lucio, F. Liu, Multipass optimal FIR filtering for processes with unknown initial states and temporary mismatches. IEEE Trans. Ind. Inf. 17(8), 5360–5368 (2021) S.Y. Zhao, Y.S. Shmaliy, J.A. Andrade-Lucio, F. Liu, Multipass optimal FIR filtering for processes with unknown initial states and temporary mismatches. IEEE Trans. Ind. Inf. 17(8), 5360–5368 (2021)
165.
Zurück zum Zitat S.Y. Zhao, Y.S. Shmaliy, F. Liu, Batch optimal FIR smoothing: increasing state informativity in nonwhite measurement noise environments. IEEE Trans. Ind. Inf. 19(5), 6993–7001 (2023) S.Y. Zhao, Y.S. Shmaliy, F. Liu, Batch optimal FIR smoothing: increasing state informativity in nonwhite measurement noise environments. IEEE Trans. Ind. Inf. 19(5), 6993–7001 (2023)
166.
Zurück zum Zitat S.Y. Zhao, J.F. Wang, Y.S. Shmaliy, F. Liu, Discrete time q-lag maximum likelihood FIR smoothing and iterative recursive algorithm. IEEE Trans. Signal Process. 69, 6342–6354 (2021)MathSciNet S.Y. Zhao, J.F. Wang, Y.S. Shmaliy, F. Liu, Discrete time q-lag maximum likelihood FIR smoothing and iterative recursive algorithm. IEEE Trans. Signal Process. 69, 6342–6354 (2021)MathSciNet
167.
Zurück zum Zitat W.X. Zheng, On a least-squares-based algorithm for identification of stochastic linear systems. IEEE Trans. Signal Process. 46(6), 1631–1638 (1998)MathSciNet W.X. Zheng, On a least-squares-based algorithm for identification of stochastic linear systems. IEEE Trans. Signal Process. 46(6), 1631–1638 (1998)MathSciNet
168.
Zurück zum Zitat Y.H. Zhou, F. Ding, Modeling nonlinear processes using the radial basis function-based state-dependent autoregressive models. IEEE Signal Process. Lett. 27, 1600–1604 (2020) Y.H. Zhou, F. Ding, Modeling nonlinear processes using the radial basis function-based state-dependent autoregressive models. IEEE Signal Process. Lett. 27, 1600–1604 (2020)
169.
Zurück zum Zitat Y.H. Zhou, F. Ding, A novel coupled recursive multivariate nonlinear time-series modelling method by using interactive identification. Appl. Math. Modell. 127, 571–587 (2024) Y.H. Zhou, F. Ding, A novel coupled recursive multivariate nonlinear time-series modelling method by using interactive identification. Appl. Math. Modell. 127, 571–587 (2024)
170.
Zurück zum Zitat Y.H. Zhou, K.V. Ling, Online network-based identification and its application in satellite attitude control systems. IEEE Trans. Aerosp. Electron. Syst. 59(3), 2530–2543 (2023) Y.H. Zhou, K.V. Ling, Online network-based identification and its application in satellite attitude control systems. IEEE Trans. Aerosp. Electron. Syst. 59(3), 2530–2543 (2023)
171.
Zurück zum Zitat Y.H. Zhou, X. Zhang, Hierarchical estimation approach for RBF-AR models with regression weights based on the increasing data length. IEEE Trans. Circuits Syst. II Express Briefs 68(12), 3597–3601 (2021) Y.H. Zhou, X. Zhang, Hierarchical estimation approach for RBF-AR models with regression weights based on the increasing data length. IEEE Trans. Circuits Syst. II Express Briefs 68(12), 3597–3601 (2021)
Metadaten
Titel
Filtering-Based Bias-Compensation Recursive Estimation Algorithm for an Output Error Model with Colored Noise
verfasst von
Zhenwei Shi
Lincheng Zhou
Haodong Yang
Xiangli Li
Mei Dai
Publikationsdatum
31.05.2024
Verlag
Springer US
Erschienen in
Circuits, Systems, and Signal Processing / Ausgabe 9/2024
Print ISSN: 0278-081X
Elektronische ISSN: 1531-5878
DOI
https://doi.org/10.1007/s00034-024-02730-1