Event-triggered optimal adaptive control algorithm for continuous-time nonlinear systems

2014 ◽  
Vol 1 (3) ◽  
pp. 282-293 ◽  
IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 141062-141071 ◽  
Author(s):  
Xiaofei Zhang ◽  
Hongbin Ma ◽  
Xinghong Zhang ◽  
You Li

2015 ◽  
Vol 740 ◽  
pp. 247-250
Author(s):  
Feng Qiao ◽  
Zhi Zhen Liu

In this paper, a multi-level adaptive control algorithm using parameters self-tuning is proposed for improving the tracking performance of a class of SISO nonlinear systems. This scheme is comprised of the pseudo partial derivative estimation law and the adaptive control law. The adaptive control law is derived from a novel higher order weighted one-step-ahead criterion function which exploits more previous control information. In order to identify the laws’ penalty factors which partly imply the dynamics of the system, an approach of parameters self-tuning is proposed with on-line recursive gradient algorithm. This design is model free and depends directly on the pseudo partial derivative updating on-line with the input and output data Simulation examples are provided to illustrate the effectiveness of the proposed method.


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