Previous best input based first order D-type iterative learning control for nonlinear system with high order relative degree

2016 ◽  
Author(s):  
Yi Liu ◽  
Shan Liu
Keyword(s):  
Nonlinear System ◽  
Iterative Learning Control ◽  
Learning Control ◽  
Iterative Learning ◽  
High Order ◽  
Relative Degree ◽  
First Order

scholarly journals High-Order Feedback Iterative Learning Control Algorithm with Forgetting Factor

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Hongbin Wang ◽  
Jian Dong ◽  
Yueling Wang
Keyword(s):  
Nonlinear System ◽  
Iterative Learning Control ◽  
Control Algorithm ◽  
Learning Control ◽  
Iterative Learning ◽  
High Order ◽  
Forgetting Factor ◽  
Trajectory Simulation ◽  
Number Of Iterations

A novel iterative learning control (ILC) algorithm is proposed to produce output curves that pass close to the desired trajectory. The key advantage of the proposed algorithm is introducing forgetting factor, which is a function of the number of iterations. Due to the forgetting factor characteristic of ILC, the proposed scheme not only stabilizes the nonlinear system with uncertainties but also weakens interference on the tracking desired trajectory. Simulation examples are included to demonstrate feasibility and effectiveness of the proposed algorithm.

scholarly journals Iterative Learning Control for High-Order Systems With Arbitrary Initial Shifts

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 5147-5159
Author(s):  
Guojun Li ◽  
Yu Zhang ◽  
Kang Wang ◽  
Dongjie Chen
Keyword(s):  
Iterative Learning Control ◽  
Learning Control ◽  
Iterative Learning ◽  
High Order
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