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- W4386567727 abstract "This paper presents an adaptive fixed-time inverse optimal control strategy for multi-agent systems with unknown dynamics. Instead of directly solving the Hamilton-Jacobi-Bellman equation to obtain the optimal control law, we prove that a meaningful performance function can be minimized by the corresponding controller, which is obtained using the backstepping technique. As a result, the complex solving process is avoided, leading to significant savings in computational resources and learning time. To handle the unknown system dynamics, fuzzy logic systems are employed. Additionally, an auxiliary Lyapunov function is defined, which allows us to deduce that the consensus tracking errors of the multi-agent system converge to a specified region within a fixed time. The efficiency of the proposed method is demonstrated through simulation results." @default.
- W4386567727 created "2023-09-10" @default.
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- W4386567727 date "2023-09-01" @default.
- W4386567727 modified "2023-09-28" @default.
- W4386567727 title "Distributed Fuzzy Inverse Optimal Fixed-time Control for Uncertain Multi-agent Systems" @default.
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- W4386567727 doi "https://doi.org/10.1016/j.ins.2023.119670" @default.
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