Abstract
Aiming at the uncertain parameters and transient instability of the system caused by the actuator fault of the multiagent system, this article adopts the radial basis function neural networks to approximate unknown nonlinear function. Then, a novel adaptive fault-tolerant controller is designed based on the combination back-stepping technology and dynamic surface technology to compensate the unknown nonlinear hybrid actuator faults, thereby improving the fault tolerance of the system. Furthermore, the designed controller can guarantee the transient stability of the system through finite-time theory and Lyapunov stability theory. Finally, the comparison of two simulation examples is given to verify the effectiveness of the designed controller, which provided an effective research idea for engineering practice.
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