Adaptive Backstepping Output Feedback Control for SISO Nonlinear System Using Fuzzy Neural Networks

Shao-Cheng Tong; Yong-Ming Li

doi:10.1007/s11633-009-0145-0

Adaptive Backstepping Output Feedback Control for SISO Nonlinear System Using Fuzzy Neural Networks

doi: 10.1007/s11633-009-0145-0

1.
Department of Basic Mathematics, Liaoning University of Technology, Jinzhou 121001, PRC

基金项目:

supported by National Natural Science Foundationof China (No.60674056);National Key Basic Research and Devel-opment Program of China (No.2002CB312200);Outstanding YouthFunds of Liaoning Province (No.2005219001);Educational De-partment of Liaoning Province (No.2006R29 and No.2007T80)

Adaptive Backstepping Output Feedback Control for SISO Nonlinear System Using Fuzzy Neural Networks

1.
Department of Basic Mathematics, Liaoning University of Technology, Jinzhou 121001, PRC

Funds:

摘要: In this paper, a new fuzzy-neural adaptive control approach is developed for a class of single-input and single-output (SISO) nonlinear systems with unmeasured states. Using fuzzy neural networks to approximate the unknown nonlinear functions, a fuzzy- neural adaptive observer is introduced for state estimation as well as system identification. Under the framework of the backstepping design, fuzzy-neural adaptive output feedback control is constructed recursively. It is proven that the proposed fuzzy adaptive control approach guarantees the global boundedness property for all the signals, driving the tracking error to a small neighbordhood of the origin. Simulation example is included to illustrate the effectiveness of the proposed approach.
- Nonlinear systems /
- backstepping control /
- adaptive fuzzy neural networks control /
- state observer /
- output feedback control
Abstract: In this paper, a new fuzzy-neural adaptive control approach is developed for a class of single-input and single-output (SISO) nonlinear systems with unmeasured states. Using fuzzy neural networks to approximate the unknown nonlinear functions, a fuzzy- neural adaptive observer is introduced for state estimation as well as system identification. Under the framework of the backstepping design, fuzzy-neural adaptive output feedback control is constructed recursively. It is proven that the proposed fuzzy adaptive control approach guarantees the global boundedness property for all the signals, driving the tracking error to a small neighbordhood of the origin. Simulation example is included to illustrate the effectiveness of the proposed approach.
- Nonlinear systems /
- backstepping control /
- adaptive fuzzy neural networks control /
- state observer /
- output feedback control

[1]	L.X.Wang.Adaptive fuzzy Systems and Control:Design and Stability Analysis,Englewood Cliffs,PrenticeHall,New Jersey,USA,1994.
[2]	C.Y.Su,Y.Stepanenko.Adaptive Control of a Class of Nonlinear Systems with Fuzzy Logic.IEEE Transactions on Fuzzy Systems,vol.2,no.4,pp.285-294,1994.
[3]	B.S.Chen,C.H.Lee,Y.C.Chang.Tracking Design of Uncertain Nonlinear SISO Systems:Adaptive Fuzzy Approach.IEEE Transactions on Fuzzy Systems,vol 4,no.1,pp.32-43,1996.
[4]	J.T.Spooner,K.M.Passino.Stable Adaptive Control Using Fuzzy Systems and Neural Networks.IEEE Transactions on Fuzzy Systems,vol.4,no.3,pp.339-359,1996.
[5]	S.C.Tong,Q.Li,T.Y.Chai.Fuzzy Adaptive Control for a Class of Nonlinear Systems.Fuzzy Sets and Systems,vol.101,no.1,pp.31-39,1999.
[6]	T.Y.Chai,S.C.Tong.Fuzzy Direct Adaptive Control for a Class of Nonlinear Systems.Fuzzy Sets and Systems,vol.103,no.3,pp.379-387,1999.
[7]	R.Ordones,K.M.Passino.Stable Multi-input Multioutput Adaptive Fuzzy/Neural Control.IEEE Transactions on Fuzzy Systems,vol.7,no.3,pp.345-353,1999.
[8]	Y.C.Yang.Robust Tracking Control of Nonlinear MIMO Systems via Fuzzy Approaches.Automatics,vol.36,no.10,pp.1535-1545,2000.
[9]	H.X.Li,S.C.Tong.A Hybrid Adaptive Fuzzy Control for a Class of Nonlinear MIMO Systems.IEEE Transactions on Fuzzy Systems,vol.11,no.1,pp.24-34,2003.
[10]	C.S.Chiu.Mixed Feedforward/Feedback Based Adaptive Fuzzy Control for a Class of MIMO Nonlinear Systems IEEE Transactions on Fuzzy Systems,vol.14,no.6,pp.716-727,2006.
[11]	Y.G.Leu,W.Y.Wang.Observer-based Adaptive Fuzzy neural Control for Unknown Nonlinear Dynamical Systems IEEE Transactions on Systems,Man,and Cybernetics Part B,vol 29,no.5,pp.583-591,1999.
[12]	N.Golea,A.Golea,K.Benmahammed.Stable Indi Fuzzy Adaptive control.Fuzzy Sets and Systems,vol.1 no.3,pp.353-366,2003.
[13]	W.Y.Wang,Y.G.Leu,T.T.Lee.Output-feedback C trol of Nonlinear Systems Using Direct Adaptive Fuzzy neural Controller.Fuzzy Sets and Systems,vol.140,no.pp.341-358,2003.
[14]	S.C.Tong,H.X.Li,W.Wang.Comments on Direct Adaptive Fuzzy-neural Control with State Observer and Supervisory Controller for Unknown Nonlinear Dynamical Systems.IEEE Transactions on Fuzzy Systems,vol.11,no.5,pp.703-705,2003.
[15]	S.C.Tong,H.X.Li,W.Wang.Observer-based Adaptive Fuzzy Control for SISO Nonlinear Systems.Fuzzy Sots and Systems,vol.148,no.3,pp.355-376,2004.
[16]	N.Goléa,A.Goléa,K.Barra.Observer-based Adaptive Control of Robot Manipulators:Fuzzy Systems Approach.Applied.Soft Computing,vol.8,no.1,pp.778-787,2008.
[17]	M.Kristic,I.Kanellakopoulos,P.V.Kokotovic.Nonlinear and Adaptive Control Design,Wiley,New York,USA,1995.
[18]	Y.S.Yang,G.Feng,J.S.Ren.A Combined Backstepping and Small-gain Approach to Robust Adaptive Fuzzy Control for Strict-feedback Nonlinear Systems.IEEE Transactions on Systems,Man,and Cybernetics-Part A,vol.34,no.3,pp.406-420,2004.
[19]	Y.S.Yang,C.J.Zhou.Adaptive Fuzzy H_∞ Stabilization for Strict-feedback Canonical Nonlinear Systems via Backstepping and Small-gain Approach.IEEE Transactions on Fuzzy Systems,vol.13,no.1,pp.104-114,2005.
[20]	S.S.Zhou,G.Feng,C.B.Feng.Robust Control for a Class of Uncertain Nonlinear Systems:Adaptive Fuzzy Approach Based on Backstepping.Fuzzy Sets and Systems,vol.151,no.1,pp.1-20,2005.
[21]	M.Wang,B.Chen,S.L.Dai.Direct Adaptive Fuzzy Tracking Control for a Class of Perturbed Strict-feedback Nonlinear Systems.Fuzzy Sets and Systems,vol.158,no.24,pp.2655-2670,2007.
[22]	S.C.Tong,Y.M.Li.Direct Adaptive Fuzzy Backstepping Control for a Class Nonlinear Systems.International Journal of Innovative Computing,Information and Control,vol.3,no.4,pp.887-896,2007.
[23]	S.Jagannnathan,F.L.Lewis.Robust Backstepping Control of a Class of Nonlinear Systems Using Fuzzy Logic.Information Sciences,vol.123,no.3-4,pp.223-240,2000.
[24]	B.Chen,X.P.Liu.Fuzzy Approximate Disturbance Decoupling of MIMO Nonlinear Systems by Backstepping and Application to Chemical Processes.IEEE Transactions on Fuzzy.Systems,vol.13,no.6,pp.832-847,2005.
[25]	B.Chen,X.P Liu.Fuzzy Approximate Disturbance Decoupling of MIMO Nonlinear Systems by Backstepping Approach.Fuzzy Sets and Systems,vol.158,no.10,pp.1097-1125,2007.
[26]	J.Y.Choi,J.A.Farrell.Adaptive Observer Backstepping Control Using Neural Networks.IEEE Transactions on Neural Networks,vol.12,no.5,pp.1103-1112,2001.

[1]	Amir Hossein Davaie Markazi, Mohammad Maadani, Seyed Hassan Zabihifar, Nafiseh Doost-Mohammadi. Adaptive Fuzzy Sliding Mode Control of Under-actuated Nonlinear Systems . International Journal of Automation and Computing, 2018, 15(3): 364-376. doi: 10.1007/s11633-017-1108-5
[2]	Mahnaz Hashemi, Javad Askari, Jafar Ghaisari, Marzieh Kamali. Robust Adaptive Actuator Failure Compensation for a Class of Uncertain Nonlinear Systems . International Journal of Automation and Computing, 2017, 14(6): 719-728. doi: 10.1007/s11633-016-1016-0
[3]	Xiao-Yi Wang, Guang-Ren Duan. A Direct Parametric Approach to Spacecraft Attitude Tracking Control . International Journal of Automation and Computing, 2017, 14(5): 626-636. doi: 10.1007/s11633-017-1089-4
[4]	Xiao-Jing Wu, Xue-Li Wu, Xiao-Yuan Luo. Adaptive Neural Network Dynamic Surface Control for a Class of Nonlinear Systems with Uncertain Time Delays . International Journal of Automation and Computing, 2016, 13(4): 409-416. doi: 10.1007/s11633-015-0945-3
[5]	Tuo Zhou, Xi-Qin He. An Improved H_∞ Filter Design for Nonlinear Systems Described by T-S Fuzzy Models with Time-varying Delay . International Journal of Automation and Computing, 2015, 12(6): 671-678. doi: 10.1007/s11633-015-0930-x
[6]	Zhong-Ping Jiang, Teng-Fei Liu. A Survey of Recent Results in Quantized and Event-based Nonlinear Control . International Journal of Automation and Computing, 2015, 12(5): 455-466. doi: 10.1007/s11633-015-0906-x
[7]	Cai-Xue Chen, Yun-Xiang Xie, Yong-Hong Lan. Backstepping Control of Speed Sensorless Permanent Magnet Synchronous Motor Based on Slide Model Observer . International Journal of Automation and Computing, 2015, 12(2): 149-155. doi: 10.1007/s11633-015-0881-2
[8]	Alessandro di Gaeta, Umberto Montanaro. Application of a Robust Model Reference Adaptive Control Algorithm to a Nonlinear Automotive Actuator . International Journal of Automation and Computing, 2014, 11(4): 377-391. doi: 10.1007/s11633-014-0803-8
[9]	Guo-Dong Zhao, Na Duan. A Continuous State Feedback Controller Design for High-order Nonlinear Systems with Polynomial Growth Nonlinearities . International Journal of Automation and Computing, 2013, 10(4): 267-274. doi: 10.1007/s11633-013-0720-2
[10]	Hassan A. Yousef, Mohamed Hamdy. Observer-based Adaptive Fuzzy Control for a Class of Nonlinear Time-delay Systems . International Journal of Automation and Computing, 2013, 10(4): 275-280. doi: 10.1007/s11633-013-0721-1
[11]	Lei-Po Liu, Zhu-Mu Fu, Xiao-Na Song. Sliding Mode Control with Disturbance Observer for Class of Nonlinear Systems . International Journal of Automation and Computing, 2012, 9(5): 487-491. doi: 10.1007/s11633-012-0671-z
[12]	Chang-Liang Liu, Shao-Cheng Tong, Yong-Ming Li, Yuan-Qing Xia. Adaptive Fuzzy Backstepping Output Feedback Control of Nonlinear Time-delay Systems with Unknown High-frequency Gain Sign . International Journal of Automation and Computing, 2011, 8(1): 14-22. doi: 10.1007/s11633-010-0549-x
[13]	Xu-Dong Zhao, Qing-Shuang Zeng. H_∞ Output Feedback Control for Stochastic Systems with Mode-dependent Time-varying Delays and Markovian Jump Parameters . International Journal of Automation and Computing, 2010, 7(4): 447-454. doi: 10.1007/s11633-010-0526-4
[14]	Shao-Cheng Tong, Ning Sheng. Adaptive Fuzzy Observer Backstepping Control for a Class of Uncertain Nonlinear Systems with Unknown Time-delay . International Journal of Automation and Computing, 2010, 7(2): 236-246. doi: 10.1007/s11633-010-0236-y
[15]	Ming-Zhe Hou, Ai-Guo Wu, Guang-Ren Dua. Robust Output Feedback Control for a Class of Nonlinear Systems with Input Unmodeled Dynamics . International Journal of Automation and Computing, 2008, 5(3): 307-312. doi: 10.1007/s11633-008-0307-5
[16]	Ling-Lai Li, Dong-Hua Zhou, Ling Wang. Fault Diagnosis of Nonlinear Systems Based on Hybrid PSOSA Optimization Algorithm . International Journal of Automation and Computing, 2007, 4(2): 183-188. doi: 10.1007/s11633-007-0183-4
[17]	Sing Kiong Nguang, Ping Zhang, Steven X. Ding. Parity Relation Based Fault Estimation for Nonlinear Systems: An LMI Approach . International Journal of Automation and Computing, 2007, 4(2): 164-168. doi: 10.1007/s11633-007-0164-7
[18]	Jochen Aβfalg, Frank Allgöwer. Fault Diagnosis of Nonlinear Systems Using Structured Augmented State Models . International Journal of Automation and Computing, 2007, 4(2): 141-148. doi: 10.1007/s11633-007-0141-1
[19]	Min-Ze Chen, Qi Zhao, Dong-Hua Zhou. A Robust Fault Detection Approach for Nonlinear Systems . International Journal of Automation and Computing, 2006, 3(1): 23-28. doi: 10.1007/s11633-006-0023-y
[20]	David H. Owens, Maria Tomas-Rodriguez, Jari J. Hatönen. Limiting Behaviour in Parameter Optimal Iterative Learning Control . International Journal of Automation and Computing, 2006, 3(3): 222-228. doi: 10.1007/s11633-006-0222-6

点击查看大图

计量

文章访问数: 5377
HTML全文浏览量: 42
PDF下载量: 2999
被引次数: 0

Adaptive Backstepping Output Feedback Control for SISO Nonlinear System Using Fuzzy Neural Networks

doi: 10.1007/s11633-009-0145-0

Adaptive Backstepping Output Feedback Control for SISO Nonlinear System Using Fuzzy Neural Networks

计量

Adaptive Backstepping Output Feedback Control for SISO Nonlinear System Using Fuzzy Neural Networks

doi: 10.1007/s11633-009-0145-0

1. Department of Basic Mathematics, Liaoning University of Technology, Jinzhou 121001, PRC

English Abstract

Adaptive Backstepping Output Feedback Control for SISO Nonlinear System Using Fuzzy Neural Networks

1. Department of Basic Mathematics, Liaoning University of Technology, Jinzhou 121001, PRC

全文HTML

目录

Adaptive Backstepping Output Feedback Control for SISO Nonlinear System Using Fuzzy Neural Networks

doi: 10.1007/s11633-009-0145-0

Adaptive Backstepping Output Feedback Control for SISO Nonlinear System Using Fuzzy Neural Networks

计量

出版历程

Adaptive Backstepping Output Feedback Control for SISO Nonlinear System Using Fuzzy Neural Networks

doi: 10.1007/s11633-009-0145-0

1. Department of Basic Mathematics, Liaoning University of Technology, Jinzhou 121001, PRC

English Abstract

Adaptive Backstepping Output Feedback Control for SISO Nonlinear System Using Fuzzy Neural Networks

1. Department of Basic Mathematics, Liaoning University of Technology, Jinzhou 121001, PRC

全文HTML

目录