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- W4385899462 abstract "This paper studies the optimized backstepping con-sensus control problem for uncertain nonstrict-feedback non-linear multiagent systems with intermittent actuator faults and input quantization. A fuzzy approximation-based optimal consen-sus control scheme is proposed via the reinforcement learning algorithm. Meanwhile, a time-varying constraint function is embedded into the optimized backstepping consensus design to guarantee the consensus errors converge to a preassigned residual set within the prescribed time. To overcome the difficulty of the virtual optimized controller design caused by unknown virtual control coefficients, a class of intermediate variables is designed. A modified variable separation technique is proposed to circumvent the problem of algebraic loop caused by the construction of virtual optimized controllers. Then, based on the reconstruction of unknown bounds, a fault-tolerant controller under the quantization action is developed to compensate for the impact of unknown actuator faults automatically, and achieve semiglobally ultimately uniformly bounded results. In the end, a practical example of a group of single-link manipulators is given to illustrate the validity of the presented method." @default.
- W4385899462 created "2023-08-18" @default.
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- W4385899462 date "2023-01-01" @default.
- W4385899462 modified "2023-10-15" @default.
- W4385899462 title "Variable Separation-Based Fuzzy Optimal Control for Multiagent Systems in Nonstrict-Feedback Form" @default.
- W4385899462 doi "https://doi.org/10.1109/tfuzz.2023.3302293" @default.
- W4385899462 hasPublicationYear "2023" @default.
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