Adaptive learning control for general nonlinear systems with nonuniform trial lengths, initial state deviation, and unknown control direction

2019 ◽  
Vol 29 (17) ◽  
pp. 6227-6243 ◽  
Author(s):  
Chen Liu ◽  
Dong Shen ◽  
JinRong Wang
Keyword(s):  
Nonlinear Systems ◽  
Adaptive Learning ◽  
Learning Control ◽  
Initial State ◽  
Adaptive Learning Control ◽  
Unknown Control ◽  
Unknown Control Direction ◽  
Control Direction

Indirect Adaptive Fuzzy Control for a Class of Uncertain Nonlinear Systems with Unknown Control Direction

2013 ◽  
pp. 139-154
Author(s):  
Salim Labiod ◽  
Hamid Boubertakh ◽  
Thierry Marie Guerra
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Fuzzy Control ◽  
Fuzzy Systems ◽  
Control Algorithm ◽  
Adaptive Fuzzy Control ◽  
Control Schemes ◽  
Unknown Control ◽  
Unknown Control Direction ◽  
Control Direction

In this paper, the authors propose two indirect adaptive fuzzy control schemes for a class of uncertain continuous-time single-input single-output (SISO) nonlinear dynamic systems with known and unknown control direction. Within these schemes, fuzzy systems are used to approximate unknown nonlinear functions and the Nussbaum gain technique is used to deal with the unknown control direction. This paper first presents a singularity-free indirect adaptive control algorithm for nonlinear systems with known control direction, and then this control algorithm is generalized for the case of unknown control direction. The proposed adaptive controllers are free from singularity, allow initialization to zero of all adjustable parameters of the used fuzzy systems, and guarantee asymptotic convergence of the tracking error to zero. Simulations performed on a nonlinear system are given to show the feasibility of the proposed adaptive control schemes.

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