Simulation-based design of monotonically convergent iterative learning control for nonlinear systems

• Autorzy: Delchev K.
• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

simulation-based design; iterative learning control; nonlinear dynamic systems; learning controller; feedback controller

• Wydawca: Polish Academy of Sciences, Committee of Automatic Control and Robotics
• Czasopismo: Archives of Control Sciences
• Rocznik: 2012
• Tom: Vol. 22, no. 4
• Strony: 467--480
• Opis fizyczny: Bibliogr. 19 poz., rys., tab.

Twórcy

autor

Delchev K.

• Institute of mechanics, Bulgarian Academy of Sciences, Sofia, Bulgaria,

Bibliografia

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