Discrete robust adaptive controller based on artificial neural networks

Author(s):  
Q. David Munoz ◽  
H. Daniel Sbarbaro
1995 ◽  
Vol 28 (19) ◽  
pp. 205-210
Author(s):  
H. Daniel Patiño ◽  
Ricardo Carelli ◽  
Benjamín Kuchen

2015 ◽  
Vol 39 (4) ◽  
pp. 567-578 ◽  
Author(s):  
Bi Zhang ◽  
Zhizhong Mao ◽  
Tingfeng Zhang

In this paper, a new intelligent control scheme based on multiple models and neural networks is proposed to adaptively control a class of Hammerstein nonlinear systems with arbitrary deadzone input. This approach consists of a linear robust adaptive controller, multiple neural networks-based nonlinear adaptive controllers and a switching mechanism. Since the control input is derived from a modified certainty equivalent principle, the manner in which the closed-loop stability is established forms the main contribution. To show the usefulness of the developed results, three simulation examples, including a direct current motor subject to a nonlinear friction, are studied.


Author(s):  
Đổng Sĩ Thiên Châu ◽  
Trần Thị Hoàng Oanh ◽  
Nguyễn Ngọc Khai ◽  
Nguyễn Hoàng Minh

Author(s):  
Kobiljon Kh. Zoidov ◽  
◽  
Svetlana V. Ponomareva ◽  
Daniel I. Serebryansky ◽  
◽  
...  

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