Adaptive asymptotic tracking control of constrained multi‐input multi‐output nonlinear systems via event‐triggered strategy

2020 ◽  
Author(s):  
Ting Lei ◽  
Wenchao Meng ◽  
Kai Zhao ◽  
Long Chen
Keyword(s):  
Nonlinear Systems ◽  
Tracking Control ◽  
Asymptotic Tracking ◽  
Event Triggered

scholarly journals Neural Network-Based Event-triggered Adaptive Asymptotic Tracking Control for Switched Nonlinear Systems

2021 ◽  
Author(s):  
Baomin Li ◽  
Jianwei Xia ◽  
Wei Sun ◽  
Hao Shen ◽  
Huasheng Zhang
Keyword(s):  
Neural Network ◽  
Nonlinear Systems ◽  
Tracking Control ◽  
Tracking Error ◽  
Network Control ◽  
Switched Nonlinear Systems ◽  
Unknown Control Directions ◽  
Asymptotic Tracking ◽  
Unknown Control ◽  
Event Triggered

Abstract This paper addresses the event-triggered based adaptive asymptotic tracking control problem for switched nonlinear systems with unknown control directions based on neural network technique. A novel asymptotic tracking controller, in which Nussbaum functions are introduced to address the issue of unknown control directions, is designed by combining neural network control technology and event-triggered strategy. Different from the existing tracking control schemes, the proposed controller in this paper can guarantee that the tracking error ς 1 asymptotically converges to the origin and reduce the communication burden from the controller to the actuator. Finally, the effectiveness of the presented control design is proved by numerical examples.

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