Abstract
In this paper, a new adaptive iterative learning control method (AILC) is presented for speed and position tracking of a subway train using multiple-point-mass dynamic model. A composite energy function technique is utilized to obtain the asymptotic convergence of tracking error in the iteration axis for the proposed controller for subway trains. Then a speed constraint adaptive iterative learning control algorithm (CAILC) is designed to avoid over speed, derailment and collision of the subway train for the subway train over-speed protection. Finally, two simulation examples are given for the subway train system to show the effectiveness of theoretical studies.
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More From: IEEE Transactions on Intelligent Transportation Systems
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