ABSTRACT
This paper is concerned with the design of an adaptive fuzzy dynamic surface control for uncertain nonlinear pure-feedback systems with input and state constraints using a set of noisy measurements. The design approach is described as follows. The nonlinear uncertainties are approximated by using the fuzzy logic systems at the first stage, secondly the adaptive fuzzy dynamic surface control is introduced to remove the problem of the explosion of complexity for the derivation of the adaptive fuzzy backstepping control, thirdly a new saturation function for state constraints is proposed to design the controllers based on the Lyapunov function, fourthly the number of the adjustable parameters is reduced by using the simplified extended single input rule modules, and finally the weighted least squares estimator to take the estimates for the un-measurable states and the adjustable parameters is in a simplified structure designed. The proposed approach provides effective system performance in the simulation experiment.
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No potential conflict of interest was reported by the author.
Additional information
Notes on contributors
Toshio Yoshimura
Toshio Yoshimura is Professor Emeritus of the University of Tokushima, Japan. He was graduated from the Faculty of Engineering, the University of Tokushima in 1963, and received his PhD degree from Kyoto University in 1974. He has been Professor from 1982 through 2006 in the Faculty of Engineering, the University of Tokushima, and has been appointed as Dean in the faculty from 2001 through 2003. His research includes the adaptive control, fuzzy logic control, sliding mode control, and backstepping control for uncertain nonlinear systems. He received the Paper Awards in 1975 and 2017 from JSME, and was recommended as the Honorary Member in 2006 from the JSME.