Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Neural Computing and Applications
Erschienen in: Neural Computing and Applications 1/2015

01.01.2015 | Original Article

Fuzzy-approximation-based decentralized adaptive control for pure-feedback large-scale nonlinear systems with time-delay

verfasst von: Huanqing Wang, Xuebo Yang, Zhandong Yu, Kefu Liu, Xiaoping Liu

Erschienen in: Neural Computing and Applications | Ausgabe 1/2015

Einloggen

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

search-config
loading …

Abstract

This paper focuses on the problem of decentralized adaptive fuzzy control for a class of pure-feedback large-scale nonlinear systems with time-delay. By combining fuzzy logical systems’ universal approximation capability with adaptive backstepping technique, an adaptive fuzzy control scheme is proposed. It is proved that the developed controller guarantees that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded in mean square. Simulation results are provided to demonstrate the effectiveness of the proposed control scheme.
Vorheriger Artikel Adaptive fault-tolerant automatic train operation using RBF neural networks
Nächster Artikel Location selection using fuzzy-connective-based aggregation networks: a case study of the food and beverage chain industry in Taiwan

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

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

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!

Jetzt informieren
Literatur
1.
Krstić M, Kanellakopoulos I, Kokotovic PV (1995) Nonlinear and adaptive control design. Wiley, New York
2.
Shi P, Xia Y, Liu G, Rees D (2006) On designing of sliding-mode control for stochastic jump systems. IEEE Trans Autom Control 51(1):97–103CrossRefMathSciNet
3.
Wu LG, Su XJ, Shi P (2012) Sliding mode control with bounded L2 gain performance of markovian jump singular time-delay systems. Automatica 48(8):1929–1933CrossRefMathSciNetMATH
4.
5.
Jiang ZP, Hill DJ (1999) A robust adaptive backstepping scheme for nonlinear systems with unmodeled dynamics. IEEE Trans Autom Control 44(9):1705–1711CrossRefMathSciNetMATH
6.
Chen M, Ge SS, How BVE, Choo YS (2013) Robust adaptive position mooring control for marine vessels. IEEE Trans Control Syst Technol 21(2):395–409CrossRef
7.
Chen M, Ge SS, Ren BB (2011) Adaptive tracking control of uncertain MIMO nonlinear systems with input constraints. Automatica 47(3):452–455CrossRefMathSciNetMATH
8.
Hu QL, Ma GF, Xie LH (2008) Robust and adaptive variable structure output feedback control of uncertain systems with input nonlinearity. Automatica 44(4):552–559CrossRefMathSciNetMATH
9.
Zhao XD, Zhang LX, Shi P, Karimi HR (2013) Novel stability criteria for T–S fuzzy systems. IEEE Trans Fuzzy Syst 21(6):1–11CrossRef
10.
Tong SC, Chen B, Wang YF (2005) Fuzzy adaptive output feedback control for MIMO nonlinear systems. Fuzzy Sets Syst 156(2):285–299CrossRefMathSciNetMATH
11.
Wang T, Tong SC, Li YM (2013) Adaptive neural network output feedback control of stochastic nonlinear systems with dynamical uncertainties. Neural Comput Appl 23(5):1481–1494CrossRefMathSciNet
12.
Chen M, Ge SS (2013) Direct adaptive neural control for a class of uncertain nonaffine nonlinear systems based on disturbance observer. IEEE Trans Cybern 43(4):1213–1225CrossRef
13.
Tong SC, Li Y, Li YM, Liu YJ (2011) Observer-based adaptive fuzzy backstepping control for a class of stochastic nonlinear strict-feedback systems. IEEE Trans Syst Man Cybern Part B Cybern 41(6):1693–1704CrossRefMathSciNet
14.
Tong SC, Wang T, Li YM, Chen B (2012) A combined backstepping and stochastic small-gain approach to robust adaptive fuzzy output feedback control. IEEE Trans Fuzzy Syst 21(2):314–321CrossRef
15.
Liu YJ, Chen CLP, Wen GX, Tong SC (2011) Adaptive neural output feedback tracking control for a class of uncertain discrete-time nonlinear systems. IEEE Trans Neural Netw 22(7):1162–1167CrossRef
16.
Li TS, Tong SC, Feng G (2010) A novel robust adaptive fuzzy tracking control for a class of nonlinear multi-input/multi-output systems. IEEE Trans Fuzzy Syst 18(1):150–160CrossRef
17.
Bououden S, Chadli M, Allouani F, Filali S (2013) A new approach for fuzzy predictive adaptive controller design using particle swarm optimization algorithm. Int J Innov Comput Inf Control 9(9):3741–3758
18.
Sefriti S, Boumhidi J, Benyakhlef M, Boumhidi I (2013) Adaptive decentralized sliding mode neural network control of a class of nonlinear interconnected systems. Int J Innov Comput Inf Control 9(7):2941–2947
19.
Su XJ, Shi P, Wu LG, Song YD (2013) A novel control design on discrete-time Takagi–Sugeno fuzzy systems with time-varying delays. IEEE Trans Fuzzy Syst 20(6):655–671CrossRef
20.
Su XJ, Shi P, Wu LG, Nguang SK (2013) Induced \(\ell _2\) filtering of fuzzy stochastic systems with time-varying delays. IEEE Trans Cybern 43(4):1251–1264CrossRef
21.
22.
Wang D, Huang J (2002) Adaptive neural network control for a class of uncertain nonlinear systems in pure-feedback form. Automatica 38(8):1365–1372CrossRefMathSciNetMATH
23.
Wang C, Hill DJ, Ge SS, Chen GR (2006) An ISS-modular approach for adaptive neural control of pure-feedback systems. Automatica 42(5):723–731CrossRefMathSciNetMATH
24.
Zhang TP, Ge SS (2008) Adaptive dynamic surface control of nonlinear systems with unknown dead zone in pure feedback form. Automatica 44(7):1895–1903CrossRefMathSciNetMATH
25.
26.
Li YM, Tong SC, Li TS (2013) Direct adaptive fuzzy backstepping control of uncertain nonlinear systems in the presence of input saturation. Neural Comput Appl 23(5):1207–1216CrossRefMathSciNet
27.
Wang HQ, Chen B, Liu XP, Liu KF, Lin C (2013) Robust adaptive fuzzy tracking control for pure-feedback stochastic nonlinear systems with input constraints. IEEE Trans Cybern 43(6):2093–2104CrossRef
28.
Wang HQ, Chen B, Lin C (2013) Adaptive neural tracking control for a class of perturbed pure-feedback nonlinear systems. Nonlinear Dyn 72(1–2):207–220CrossRefMathSciNetMATH
29.
Tong SC, Li YM, Shi P (2012) Observer-based adaptive fuzzy backstepping output feedback control of uncertain MIMO pure-feedback nonlinear systems. IEEE Trans Fuzzy Syst 20(4):771–785CrossRef
30.
Wang M, Ge SS, Hong KS (2010) Approximation-based adaptive tracking control of pure-feedback nonlinear systems with multiple unknown time-varying delays. IEEE Trans Neural Netw 21(11):804–1816
31.
Niculescu S-L (2001) Delay effects on stability: a robust control approach. Springer, London
32.
Gao H, Meng X, Chen T (2008) Stabilization of networked control systems with a new delay characterization. IEEE Trans Autom Control 53(9):2142–2148CrossRefMathSciNet
33.
Chen Y, Zheng WX (2011) Stability and L2 performance analysis of stochastic delayed neural networks. IEEE Trans Neural Netw 22(10):1662–1668CrossRef
34.
Qiu J, Feng G, Yang J (2009) A new design of delay-dependent robust H-infinity filtering for discrete-time T–S fuzzy systems with time-varying delay. IEEE Trans Fuzzy Syst 17(5):1044–1058CrossRef
35.
Hua CC, Liu PX, Guan XP (2009) Backstepping control for nonlinear systems with time delays and applications to chemical reactor systems. IEEE Trans Ind Electron 56(9):3723–3732CrossRef
36.
Jiao X, Shen T (2005) Adaptive feedback control of nonlinear timedelay systems: the LaSalle–Razumikhin-based approach. IEEE Trans Autom Control 50(11):1909–1913CrossRefMathSciNet
37.
Ge SS, Hong F, Lee TH (2003) Adaptive neural network control of nonlinear systems with unknown time delays. IEEE Trans Autom Control 48(11):2004–2010CrossRefMathSciNet
38.
Chen B, Liu XP, Liu KF, Lin C (2010) Fuzzy approximation-based adaptive control of strict-feedback nonlinear systems with time delays. IEEE Trans Fuzzy Syst 18(5):883–892CrossRefMathSciNet
39.
Chen B, Liu XP, Liu KF, Lin C (2009) Novel adaptive neural control design for nonlinear MIMO time-delay systems. Automatica 45(6):1554–1560CrossRefMathSciNetMATH
40.
Wang HQ, Chen B, Lin C (2013) Adaptive neural tracking control for a class of stochastic nonlinear systems with unknown dead-zone. Int J Innov Comput Inf Control 9(8):3257–3269
41.
Datta A (1993) Performance improvement in decentralized adaptive control: a model reference scheme. IEEE Trans Autom Control 38(11):1717–1722CrossRefMATH
42.
Wen CY (1994) Decentralized adaptive regulation. IEEE Trans Autom Control 39(10):2163–2166CrossRefMATH
43.
Liu X, Huang G (2001) Global decentralized robust stabilization for interconnected uncertain nonlinear systems with multiple inputs. Automatica 37(9):1435–1442CrossRefMATH
44.
Zhang HG, Cai L (2002) Decentralized nonlinear adaptive control of an HVAC system. IEEE Trans Syst Man Cybern Part C Appl Rev 32(4):493–498CrossRef
45.
Zhou J, Wen CY (2008) Decentralized backstepping adaptive output tracking of interconnected nonlinear systems. IEEE Trans Autom Control 53(10):2378–2384CrossRefMathSciNet
46.
Tong SC, Huo BY, Li YM (2014) Observer-based adaptive decentralized fuzzy fault-tolerant control of nonlinear large-scale systems with actuator failures. IEEE Trans Fuzzy Syst 22(1):1–15CrossRef
47.
Tong SC, Liu CL, Li YM (2010) Fuzzy adaptive decentralized control for large-scale nonlinear systems with dynamical uncertainties. IEEE Trans Fuzzy Syst 18(5):845–861CrossRef
48.
Tong SC, Li YM, Zhang HG (2011) Adaptive neural network decentralized backstepping output-feedback control for nonlinear large-scale systems with time delays. IEEE Trans Neural Netw 22(7):1073–1086CrossRef
49.
Tong SC, Li YM (2013) Adaptive fuzzy decentralized output feedback control for nonlinear large-scale systems with unknown dead zone inputs. IEEE Trans Fuzzy Syst 21(5):913–925CrossRef
50.
Chen WS, Li JM (2008) Decentralized output-feedback neural control for systems with unknown interconnections. IEEE Trans Syst Man Cybern Part B Cybern 38(1):258–266CrossRef
51.
Karimi B, Menhaj MB (2010) Non-affine nonlinear adaptive control of decentralized large-scale systems using neural networks. Inf Sci 180(17):3335–3347CrossRefMathSciNetMATH
52.
Huang YS, Wu M (2011) Robust decentralized direct adaptive output feedback fuzzy control for a class of large-sale nonaffine nonlinear systems. Inf Sci 181(11):2392–2404CrossRefMATH
53.
Ge SS, Wang J (2002) Robust adaptive neural control for a class of perturbed strict feedback nonlinear systems. IEEE Trans Neural Netw 13(6):1409–1419 CrossRef
54.
Apostol TM (1963) Mathematical analysis. Addison-Wesley, Reading, MA
55.
Li J, Chen WS, Li JM (2011) Adaptive NN output-feedback decentralized stabilization for a class of large-scale stochastic nonlinear strict-feedback systems. Int J Robust Nonlinear Control 21(4):452–472CrossRefMATH
56.
Wang LX, Mendel JM (1992) Fuzzy basis functions, universal approximation, and orthogonal least squares learning. IEEE Trans Neural Netw 3(5):807–814CrossRef
Metadaten
Titel
Fuzzy-approximation-based decentralized adaptive control for pure-feedback large-scale nonlinear systems with time-delay
verfasst von
Huanqing Wang
Xuebo Yang
Zhandong Yu
Kefu Liu
Xiaoping Liu
Publikationsdatum
01.01.2015
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 1/2015
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-014-1711-0

Weitere Artikel der Ausgabe 1/2015

Neural Computing and Applications 1/2015 Zur Ausgabe

Original Article

Correlation consistency constrained matrix completion for web service tag refinement

Original Article

Location selection using fuzzy-connective-based aggregation networks: a case study of the food and beverage chain industry in Taiwan

Original Article

Artificial neural network for steganography

Original Article

Nonlinear behavior of memristive devices during tuning process and its impact on STDP learning rule in memristive neural networks

Original Article

Combining statistical analysis and artificial neural network for classifying jobs and estimating the cycle times in wafer fabrication

Original Article

Data mining-based integrated network traffic visualization framework for threat detection