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Soft Computing

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25.06.2018 | Methodologies and Application

Adaptive TOPSIS fuzzy CMAC back-stepping control system design for nonlinear systems

verfasst von: Chih-Min Lin, Tuan-Tu Huynh, Tien-Loc Le

Erschienen in: Soft Computing | Ausgabe 16/2019

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This paper aims to propose a more efficient control algorithm for nonlinear systems. A novel adaptive Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) fuzzy cerebellar model articulation controller (FCMAC) back-stepping control system is developed. The proposed adaptive TOPSIS FCMAC (ATFCMAC) incorporates a multi-criteria decision analysis with a fuzzy CMAC structure to determine the optimal threshold values for selecting suitable firing nodes, improving the computational efficiency, reducing the number of firing rules, and achieving good performance for nonlinear systems. A back-stepping technique is employed for the control system design. The proposed control system comprises an ATFCMAC and a robust compensator; the ATFCMAC is used to approximate an ideal controller and the robust compensator is used to reduce the influence of residual approximation error between the ideal controller and the ATFCMAC. The parameters of the proposed ATFCMAC are tuned online using the adaptation laws that are derived from a Lyapunov stability theorem, so that the stability of the control system is guaranteed. The simulation and experimental results for a Duffing–Holmes chaotic system and a magnetic ball levitation system are used to verify the effectiveness of the proposed control scheme.

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Abu Arqub O (2017) Adaptation of reproducing kernel algorithm for solving fuzzy Fredholm–Volterra integrodifferential equations. Neural Comput Appl 28:1591–1610CrossRef

Abu Arqub O, Mohammed A-S, Momani S, Hayat T (2016) Numerical solutions of fuzzy differential equations using reproducing kernel Hilbert space method. Soft Comput 20:3283–3302CrossRefMATH

Abu Arqub O, Al-Smadi M, Momani S, Hayat T (2017) Application of reproducing kernel algorithm for solving second-order, two-point fuzzy boundary value problems. Soft Comput 21:7191–7206CrossRefMATH

Albus JS (1975) A new approach to manipulator control: the cerebellar model articulation controller (CMAC). J Dyn Syst Meas Contr 97:220–227CrossRefMATH

Chang W-D, Yan J-J (2005) Adaptive robust PID controller design based on a sliding mode for uncertain chaotic systems. Chaos Solitons Fractals 26:167–175CrossRefMATH

Chaoui H, Gualous H (2017) Adaptive state of charge estimation of lithium-ion batteries with parameter and thermal uncertainties. IEEE Trans Control Syst Technol 25:752–759CrossRef

Chen B-S, Lee C-H, Chang Y-C (1996) Tracking design of uncertain nonlinear SISO systems: adaptive fuzzy approach. IEEE Trans Fuzzy Syst 4:32–43CrossRef

Chen P-C, Hsu C-F, Lee T-T, Wang C-H (2009) Fuzzy-identification-based adaptive backstepping control using a self-organizing fuzzy system. Soft Comput 13:635–647CrossRefMATH

Chen C-S, Tsai S-H, Tam L-M, Li S-Y (2016) Fuzzy adaptive control of two totally different chaotic systems with complicated structures by novel pragmatically adaptive control strategy. Soft Comput. https://doi.org/10.1007/s00500-016-2230-y MATH

Chiang H-K, Chen C-A, Li M-Y (2006) Integral variable-structure grey control for magnetic levitation system. IEE Proc Electr Power Appl 153:809–814CrossRef

Chiu C-H, Peng Y-F, Lin Y-W (2011) Robust intelligent backstepping tracking control for wheeled inverted pendulum. Soft Comput 15:2029–2040CrossRefMATH

Hsu CF, Lin CM, Lee TT (2006) Wavelet adaptive backstepping control for a class of nonlinear systems. IEEE Trans Neural Netw 17:1175–1183CrossRef

http://www.advantech.com.tw/products/1-2mlkc9/pci-1716

Hwang CL, Yoon K (1981) Multiple attribute decision making: methods and applications: a state-of-the-art survey. Springer, New YorkCrossRefMATH

Hwang C-L, Lai Y-J, Liu T-Y (1993) A new approach for multiple objective decision making. Comput Oper Res 20:889–899CrossRefMATH

Lin C-M, Chen T-Y (2009) Self-organizing CMAC control for a class of MIMO uncertain nonlinear systems. IEEE Trans Neural Netw 20:1377–1384CrossRef

Lin TC, Lee TY (2011) Chaos synchronization of uncertain fractional-order chaotic systems with time delay based on adaptive fuzzy sliding mode control. IEEE Trans Fuzzy Syst 19:623–635CrossRef

Lin C-M, Li H-Y (2012) TSK fuzzy CMAC-based robust adaptive backstepping control for uncertain nonlinear systems. IEEE Trans Fuzzy Syst 20:1147–1154CrossRef

Lin C-M, Li H-Y (2013) Self-organizing adaptive wavelet CMAC backstepping control system design for nonlinear chaotic systems. Nonlinear Anal Real World Appl 14:206–223MathSciNetCrossRefMATH

Lin CM, Li HY (2015) Dynamic petri fuzzy cerebellar model articulation controller design for a magnetic levitation system and a two-axis linear piezoelectric ceramic motor drive system. IEEE Trans Control Syst Technol 23:693–699CrossRef

Lin C-M, Peng Y-F, Hsu C-F (2004) Robust cerebellar model articulation controller design for unknown nonlinear systems. IEEE Trans Circuits Syst II Express Briefs 51:354–358CrossRef

Lin F-J, Chen S-Y, Shyu K-K (2009) Robust dynamic sliding-mode control using adaptive RENN for magnetic levitation system. IEEE Trans Neural Networks 20:938–951CrossRef

Lin C-M, Lin M-H, Chen C-W (2011) SoPC-based adaptive PID control system design for magnetic levitation system. IEEE Syst J 5:278–287CrossRef

Lin C-M, Liu Y-L, Li H-Y (2014) SoPC-based function-link cerebellar model articulation control system design for magnetic ball levitation systems. IEEE Trans Industr Electron 61:4265–4273CrossRef

Lin C-M, Le T-L, Huynh T-T (2018) Self-evolving function-link interval type-2 fuzzy neural network for nonlinear system identification and control. Neurocomputing 275:2239–2250CrossRef

Liu S, Zhang F (2014) Complex function projective synchronization of complex chaotic system and its applications in secure communication. Nonlinear Dyn 76:1087–1097MathSciNetCrossRefMATH

Mousavi-Nasab SH, Sotoudeh-Anvari A (2017) A comprehensive MCDM-based approach using TOPSIS, COPRAS and DEA as an auxiliary tool for material selection problems. Mater Des 121:237–253CrossRef

Niknam T, Khooban MH (2013) Fuzzy sliding mode control scheme for a class of non-linear uncertain chaotic systems. IET Sci Meas Technol 7:249–255CrossRef

Qian W, Qiang Z, Xiaopeng W (2010) Image encryption algorithm based on DNA biological properties and chaotic systems. In: 2010 IEEE fifth international conference on bio-inspired computing: theories and applications (BIC-TA), pp 132–136

Rao RV (2007) Decision making in the manufacturing environment: using graph theory and fuzzy multiple attribute decision making methods. Springer Science & Business Media, New YorkMATH

Senkerik R, Kominkova Oplatkova Z, Zelinka I, Chramcov B, Davendra DD, Pluhacek M (2014) Utilization of analytic programming for the evolutionary synthesis of the robust multi-chaotic controller for selected sets of discrete chaotic systems. Soft Comput 18:651–668CrossRef

Shannon CE (1948) A mathematical theory of communication. Bell Syst Tech J 27:379–423MathSciNetCrossRefMATH

Si J, Marjanovic-Halburd L, Nasiri F, Bell S (2016) Assessment of building-integrated green technologies: a review and case study on applications of multi-criteria decision making (MCDM) method. Sustain Cities Soc 27:106–115CrossRef

Sumsurooah S, Odavic M, Bozhko S (2016) A modeling methodology for robust stability analysis of nonlinear electrical power systems under parameter uncertainties. IEEE Trans Ind Appl 52:4416–4425CrossRef

Vaidyanathan S (2014a) Analysis and adaptive synchronization of eight-term 3-D polynomial chaotic systems with three quadratic nonlinearities. Eur Phys J Spec Top 223:1519–1529CrossRef

Vaidyanathan S (2014b) A new eight-term 3-D polynomial chaotic system with three quadratic nonlinearities. Far East J Math Sci 84:219MATH

Wang L-X (1994) Adaptive fuzzy systems and control: design and stability analysis. Prentice-Hall, Inc, Upper Saddle River

Wang E, Alp N, Shi J, Wang C, Zhang X, Chen H (2017) Multi-criteria building energy performance benchmarking through variable clustering based compromise TOPSIS with objective entropy weighting. Energy 125:197–210CrossRef

Yang Z-J, Kunitoshi K, Kanae S, Wada K (2008) Adaptive robust output-feedback control of a magnetic levitation system by K-filter approach. IEEE Trans Industr Electron 55:390–399CrossRef

Yang ZJ, Fukushima Y, Kanae S, Wada K (2009) Robust non-linear output-feedback control of a magnetic levitation system by k-filter approach. IET Control Theory Appl 3:852–864MathSciNetCrossRef

Yoon K (1987) A reconciliation among discrete compromise solutions. J Oper Res Soc 38:277–286CrossRefMATH

Yu Y, Yang Z, Han C, Liu H (2018) Fuzzy adaptive back-stepping sliding mode controller for high-precision deflection control of the magnetically suspended momentum wheel. IEEE Trans Industr Electron 65:3530–3538CrossRef

Zeleny M (1982) Multiple criteria decision making. McGraw-Hill, New YorkMATH

Titel: Adaptive TOPSIS fuzzy CMAC back-stepping control system design for nonlinear systems
verfasst von: Chih-Min Lin
Tuan-Tu Huynh
Tien-Loc Le
Publikationsdatum: 25.06.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 16/2019
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-018-3333-4

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