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Adaptive Iterative Learning Control for Nonlinear Systems with Unknown Control Gain

Jiang, Ping
; 
Chen, H.
Publication Date
2004
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Keywords
Adaptive Control, Convergence, Nonlinear Control Systems, Learning Systems, Uncertain Systems, Nonlinear Dynamical Systems, Iterative Methods, Control System Synthesis
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Accepted for publication
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Engineering and Digital Technology Publications
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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.
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http://hdl.handle.net/10454/4154
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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.
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https://doi.org/10.1115/1.1850538
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