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Consensus Tracking by Iterative Learning Control for Linear Heterogeneous Multiagent Systems Based on Fractional-Power Error Signals

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Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Institute of Automation, Jiangnan University, Wuxi 214122, China
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Shanghai Keliang Information Technology & Engineering Company , Ltd., Shanghai 200233, China
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Author to whom correspondence should be addressed.
Algorithms 2019, 12(9), 185; https://doi.org/10.3390/a12090185
Received: 25 July 2019 / Revised: 29 August 2019 / Accepted: 3 September 2019 / Published: 5 September 2019
This paper deals with the consensus tracking problem of heterogeneous linear multiagent systems under the repeatable operation environment, and adopts a proportional differential (PD)-type iterative learning control (ILC) algorithm based on the fractional-power tracking error. According to graph theory and operator theory, convergence condition is obtained for the systems under the interconnection topology that contains a spanning tree rooted at the reference trajectory named as the leader. Our algorithm based on fractional-power tracking error achieves a faster convergence rate than the usual PD-type ILC algorithm based on the integer-order tracking error. Simulation examples illustrate the correctness of our proposed algorithm. View Full-Text
Keywords: heterogeneous linear multiagent systems; consensus tracking; fractional-power tracking error; PD type iterative learning control heterogeneous linear multiagent systems; consensus tracking; fractional-power tracking error; PD type iterative learning control
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Luo, Y.-J.; Liu, C.-L.; Liu, G.-Y. Consensus Tracking by Iterative Learning Control for Linear Heterogeneous Multiagent Systems Based on Fractional-Power Error Signals. Algorithms 2019, 12, 185.

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