Model-based learning control with non-repetitive initial conditions

Author(s):  
Orest V. Iftime ◽  
Michel Verhaegen
Author(s):  
Zhi Qiang Tang ◽  
Ho Lam Heung ◽  
Xiang Qian Shi ◽  
Raymond Kai-yu Tong ◽  
Zheng Li

2012 ◽  
Vol 22 (4) ◽  
pp. 467-480
Author(s):  
Kamen Delchev

This paper deals with a simulation-based design of model-based iterative learning control (ILC) for multi-input, multi-output nonlinear time-varying systems. The main problem of the implementation of the nonlinear ILC in practice is possible inadmissible transient growth of the tracking error due to a non-monotonic convergence of the learning process. A model-based nonlinear closed-loop iterative learning control for robot manipulators is synthesized and its tuning depends on only four positive gains of both controllers - the feedback one and the learning one. A simulation-based approach for tuning the learning and feedback controllers is proposed to achieve fast and monotonic convergence of the presented ILC. In the case of excessive growth of transient errors this approach is the only way for learning gains tuning by using classical engineering techniques for practical online tuning of feedback gains


2014 ◽  
Vol 19 (9) ◽  
pp. 3255-3266 ◽  
Author(s):  
Chen Liu ◽  
Jiang Wang ◽  
Huiyan Li ◽  
Zhiqin Xue ◽  
Bin Deng ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document