Abstract
Most of the existing iterative learning control algorithms proposed for time-delay systems are based on the condition that the time-delay is precisely available, and the initial state is reset to the desired one or a fixed value at the start of each operation, which makes great limitation on the practical application of corresponding results. In this paper, a new iterative learning control algorithm is studied for a class of nonlinear system with uncertain state delay and arbitrary initial error. This algorithm needs to know only the boundary estimation of the state delay, and the initial state is updated, while the convergence of the system is guaranteed. Without state disturbance and output measurement noise, the system output will strictly track the desired trajectory after successive iteration. Furthermore, in the presence of state disturbance and measurement noise, the tracking error will be bounded uniformly. The convergence is strictly proved mathematically, and sufficient conditions are obtained. A numerical example is shown to demonstrate the effectiveness of the proposed approach.
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Hongbin WANG was born in 1966. He received his Ph.D. degree in Control Theory and Control Engineering from Yanshan University in 2005. He is currently a professor at the College of Electrical Engineering of Yanshan University. His research interests cover process automation, robot control technology, variable structure control system, robust control, and visual servo.
Yan WANG was born in 1985. She received her B.S. degree from Automation Department of Yanshan University in 2008. Currently, she is pursing her M.S. degree in the Control Theory and Control Engineering at Yanshan University. Her research interests include robotic control and iterative learning control.
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Wang, H., Wang, Y. Iterative learning control for nonlinear systems with uncertain state delay and arbitrary initial error. J. Control Theory Appl. 9, 541–547 (2011). https://doi.org/10.1007/s11768-011-9235-y
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DOI: https://doi.org/10.1007/s11768-011-9235-y