Iterative learning control for fractional-order multi-agent systems |
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| Authors: | Dahui Luo JinRong Wang Dong Shen Michal Fe?kan |
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| Institution: | 1. Department of Mathematics, Guizhou University, Guiyang, Guizhou 550025, PR China;2. College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, PR China;3. Department of Mathematical Analysis and Numerical Mathematics, Faculty of Mathematics, Physics and Informatics, Comenius University in Bratislava, Mlynská dolina, Bratislava 842 48, Slovakia;4. Mathematical Institute, Slovak Academy of Sciences, ?tefánikova 49, Bratislava 814 73, Slovakia |
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| Abstract: | In this paper, we apply iterative learning control to both linear and nonlinear fractional-order multi-agent systems to solve consensus tacking problem. Both fixed and iteration-varying communicating graphs are addressed in this paper. For linear systems, a PDα-type update law with initial state learning mechanism is introduced by virtue of the memory property of fractional-order derivative. For nonlinear systems, a Dα-type update law with forgetting factor and initial state learning is designed. Sufficient conditions for both linear and nonlinear systems are established to guarantee all agents achieving the asymptotic output consensus. Simulation examples are provided to verify the proposed schemes. |
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| Keywords: | Corresponding author |
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