Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/128608
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Type: Journal article
Title: Model-free cooperative adaptive sliding-mode-constrained-control for multiple linear induction traction systems
Author: Xu, D.
Zhang, W.
Shi, P.
Jiang, B.
Citation: IEEE Transactions on Cybernetics, 2020; 50(9):4076-4086
Publisher: IEEE
Issue Date: 2020
ISSN: 2168-2267
2168-2275
Statement of
Responsibility: 
Dezhi Xu, Weiming Zhang, Peng Shi, Bin Jiang
Abstract: In order to deal with the speed cooperative control problem in the multiple linear induction traction systems consists of multiple linear induction motors, a model-free cooperative adaptive sliding-mode-constrained-control strategy is proposed considering the input magnitude and rate constraints which may cause the problem of actuator and integral saturation. First, the equivalent circuit topology of the single motor in the system is investigated. Besides, the system is considered as the multiagent system with fixed communication topology due to the interaction between adjacent motors. Then, the output observer is presented to estimate the output and the estimation algorithm of pseudo-partial derivative parameter and uncertainties is proposed. Based on the above, the proposed control scheme is presented by designing an integral sliding-mode surface containing the systematic error and an anti-windup compensator is added to eliminate the saturation. Finally, the simulations of the proposed control strategy for multiagent systems are carried out to demonstrate the effectiveness and superiority of the proposed control strategy.
Keywords: Cooperative adaptive control; model-free constrained control; multiagent systems; multiple linear induction traction systems (multi-LITSs); systematic error
Rights: © 2019 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.
DOI: 10.1109/TCYB.2019.2913983
Grant ID: http://purl.org/au-research/grants/arc/DP170102644
Published version: http://dx.doi.org/10.1109/tcyb.2019.2913983
Appears in Collections:Aurora harvest 8
Computer Science publications

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