Adaptive neural tracking control for switched nonlinear systems with state quantization

2021 ◽  
Author(s):  
Danping Zeng ◽  
Zhi Liu ◽  
C.L.Philip Chen ◽  
Yun Zhang
Automatica ◽  
2015 ◽  
Vol 52 ◽  
pp. 185-191 ◽  
Author(s):  
Xudong Zhao ◽  
Xiaolong Zheng ◽  
Ben Niu ◽  
Liang Liu

2019 ◽  
Vol 490 ◽  
pp. 369-386 ◽  
Author(s):  
Xin Huo ◽  
Li Ma ◽  
Xudong Zhao ◽  
Ben Niu ◽  
Guangdeng Zong

2020 ◽  
Vol 42 (13) ◽  
pp. 2482-2491
Author(s):  
Shan-Liang Zhu ◽  
De-Yu Duan ◽  
Lei Chu ◽  
Ming-Xin Wang ◽  
Yu-Qun Han ◽  
...  

In this paper, a multi-dimensional Taylor network (MTN)-based adaptive tracking control approach is proposed for a class of switched nonlinear systems with input nonlinearity. Firstly, the input nonlinearity is assumed to be bounded by a sector interval. Secondly, with the help of MTNs approximating the unknown nonlinear functions, a novel adaptive MTN control scheme has the advantages of low cost, simple structure and real time feature is developed via backstepping technique. It is shown that the tracking error finally converges to a small domain around the origin and all signals in the closed-loop system are bounded. Finally, two examples are given to demonstrate the effectiveness of the proposed control scheme.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 204782-204790 ◽  
Author(s):  
Yi Chang ◽  
Shuo Zhang ◽  
N. D. Alotaibi ◽  
A. F. Alkhateeb

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