DYNAMIC SURFACE CONTROL APPROACH TO ADAPTIVE ROBUST CONTROL OF NONLINEAR SYSTEMS IN SEMI-STRICT FEEDBACK FORM

2005 ◽  
Vol 38 (1) ◽  
pp. 1154-1159 ◽  
Author(s):  
Zi-Jiang Yang ◽  
Toshimasa Nagai ◽  
Shunshoku Kanae ◽  
Kiyoshi Wada
Keyword(s):  
Robust Control ◽  
Nonlinear Systems ◽  
Dynamic Surface Control ◽  
Adaptive Robust Control ◽  
Feedback Form ◽  
Dynamic Surface ◽  
Control Approach ◽  
Surface Control ◽  
Strict Feedback

scholarly journals Adaptive Robust Control for Networked Strict-Feedback Nonlinear Systems with State and Input Quantization

Electronics ◽  
2021 ◽  
Vol 10 (22) ◽  
pp. 2783
Author(s):  
Yanbin Liu ◽  
Jue Wang ◽  
Luis Gomes ◽  
Weichao Sun
Keyword(s):  
Robust Control ◽  
Nonlinear Systems ◽  
Networked Control Systems ◽  
Tracking Error ◽  
Adaptive Robust Control ◽  
Feedback Form ◽  
Control Approach ◽  
Input Quantization ◽  
The Stability ◽  
Strict Feedback

Backstepping method is a successful approach to deal with the systems in strict-feedback form. However, for networked control systems, the discontinuous virtual law caused by state quantization introduces huge challenges for its applicability. In this article, a quantized adaptive robust control approach in backsetpping framework is developed in this article for networked strict-feedback nonlinear systems with both state and input quantization. In order to prove the efficiency of the designed control scheme, a novel form of Lyapunov candidate function was constructed in the process of analyzing the stability, which is applicable for the systems with nondifferentiable virtual control law. In particular, the state and input quantizers can be in any form as long as they meet the sector-bound condition. The theoretic result shows that the tracking error is determined by the pregiven constants and quantization errors, which are also verified by the simulation results.

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