Adaptive fuzzy dynamic surface control for uncertain nonlinear systems in pure-feedback form with input and state constraints using noisy measurements

2018 ◽  
Vol 50 (1) ◽  
pp. 104-115 ◽  
Author(s):  
Toshio Yoshimura
Keyword(s):  
Nonlinear Systems ◽  
State Constraints ◽  
Dynamic Surface Control ◽  
Uncertain Nonlinear Systems ◽  
Feedback Form ◽  
Dynamic Surface ◽  
Adaptive Fuzzy ◽  
Surface Control ◽  
Noisy Measurements ◽  
Input And State Constraints

Adaptive fuzzy dynamic surface control for uncertain discrete-time nonlinear systems in pure-feedback form using a set of noisy measurements

2017 ◽  
Vol 24 (13) ◽  
pp. 2912-2926 ◽  
Author(s):  
Toshio Yoshimura
Keyword(s):  
Nonlinear Systems ◽  
Discrete Time ◽  
Weighted Least Squares ◽  
Dynamic Surface Control ◽  
Feedback Form ◽  
Dynamic Surface ◽  
Adaptive Fuzzy ◽  
Surface Control ◽  
Single Input ◽  
Noisy Measurements

This paper is concerned with the design of an adaptive fuzzy dynamic surface control for multi-input multi-output uncertain discrete-time nonlinear systems in pure-feedback form. The states of the systems are observed with independent measurement noises. The design approach of the proposed adaptive fuzzy dynamic surface control is described as follows. By applying the theory of the adaptive fuzzy dynamic surface control, the problem of the explosion of complexity due to the repeated differentials of nonlinear functions is removed so that the controller is simplified in a structure at the first stage; second, the number of the adjustable parameters is reduced by using the simplified extended single-input rule modules; and, finally, the simplified weighted least squares estimator is designed to take the estimates for the unmeasurable states and the adjustable parameters. The simulation experiment for a simple numerical system provides the effectiveness of the proposed approach.

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