Adaptive Iterative Learning Control for Nonlinear Systems with Unknown Control Gain

Jiang, Ping; Chen, H.

Publication date

2004

Author

Jiang, Ping
Chen, H.

Keyword

Adaptive Control
Convergence
Nonlinear Control Systems
Learning Systems
Uncertain Systems
Nonlinear Dynamical Systems
Iterative Methods
Control System Synthesis

Peer-Reviewed

Yes

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Abstract

An adaptive iterative learning control approach is proposed for a class of single-input single-output uncertain nonlinear systems with completely unknown control gain. Unlike the ordinary iterative learning controls that require some preconditions on the learning gain to stabilize the dynamic systems, the adaptive iterative learning control achieves the convergence through a learning gain in a Nussbaum-type function for the unknown control gain estimation. This paper shows that all tracking errors along a desired trajectory in a finite time interval can converge into any given precision through repetitive tracking. Simulations are carried out to show the validity of the proposed control method.

URI

http://hdl.handle.net/10454/4154

Version

No full-text available in the repository

Citation

Jian, P. and Chen, H. (2004). Adaptive Iterative Learning Control for Nonlinear Systems with Unknown Control Gain. Journal of Dynamic Systems Measurement and Control. Vol. 126, No. 4, pp. 916-921.

Link to Version of Record

https://doi.org/10.1115/1.1850538

Type

Article

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