An Associatively Recursive Dynamic Backstepping Control Design for Pure-Feedback Nonlinear Systems

2021 ◽  
Author(s):  
Sheng Zhang ◽  
Xin Du ◽  
Fang-Fang Hu ◽  
Jiang-Tao Huang
Keyword(s):  
Nonlinear Systems ◽  
Control Design ◽  
Backstepping Control

Adaptive Neural Backstepping Control Design for A Class of Nonsmooth Nonlinear Systems

2019 ◽  
Vol 49 (9) ◽  
pp. 1820-1831 ◽  
Author(s):  
Xudong Zhao ◽  
Xinyong Wang ◽  
Shuo Zhang ◽  
Guangdeng Zong
Keyword(s):  
Nonlinear Systems ◽  
Control Design ◽  
Backstepping Control

scholarly journals Dynamic Feedback Backstepping Control for a Class of MIMO Nonaffine Block Nonlinear Systems

2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
Hai-Yan Li ◽  
Yun-An Hu ◽  
Jian-Cun Ren ◽  
Min Zhu
Keyword(s):  
Nonlinear Systems ◽  
Feedback Linearization ◽  
Closed Loop ◽  
Sliding Mode ◽  
Design Method ◽  
Control Design ◽  
Backstepping Control ◽  
Dynamic Feedback ◽  
Closed Loop System ◽  
Linearization Techniques

For a class of MIMO nonaffine block nonlinear systems, a neural network- (NN-) based dynamic feedback backstepping control design method is proposed to solve the tracking problem. This problem is difficult to be dealt with in the control literature, mainly because the inverse controls of block nonaffine systems are not easy to resolve. To overcome this difficulty, dynamic feedback, backstepping design, sliding mode-like technique, NN, and feedback linearization techniques are incorporated to deal with this problem, in which the NNs are used to approximate and adaptively cancel the uncertainties. It is proved that the whole closed-loop system is stable in the sense of Lyapunov. Finally, simulations verify the effectiveness of the proposed scheme.

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