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Adaptive backstepping output feedback control for SISO nonlinear system using fuzzy neural networks

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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.

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Authors and Affiliations

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

    Shao-Cheng Tong & Yong-Ming Li

Authors
  1. Shao-Cheng Tong
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  2. Yong-Ming Li
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Corresponding author

Correspondence to Shao-Cheng Tong.

Additional information

This work was supported by National Natural Science Foundation of China (No. 60674056) and National Key Basic Research and Development Program of China (No. 2002CB312200), Outstanding Youth Funds of Liaoning Province (No. 2005219001), and Educational Department of Liaoning Province (No. 2006R29 and No. 2007T80).

Shao-Cheng Tong graduated from Jinzhou Normal College, PRC, in 1982. He received the M. Sc. degree from Dalian Marine University in 1988 and the Ph.D. degree from Northeastern University, PRC, in 1997. He is currently a professor at the Department of Basic Mathematics, Liaoning University of Technology, China.

His research interests include fuzzy control theory and nonlinear adaptive control.

Yong-Ming Li graduated from Liaoning University of Technology, PRC, in 2004. He received the M. Sc. degree from Liaoning University of Technology, PRC, in 2007. He is currently an assistant in the Department of Basic Mathematics, Liaoning University of Technology.

His research interests include fuzzy control theory, nonlinear adaptive control, and intelligent control.

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Tong, SC., Li, YM. Adaptive backstepping output feedback control for SISO nonlinear system using fuzzy neural networks. Int. J. Autom. Comput. 6, 145–153 (2009). https://doi.org/10.1007/s11633-009-0145-0

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