Addressing the susceptibility of doubly fed induction generators(DFIG)to external disturbances that adversely affect power grid,recurrent Legendre fuzzy neural network(RLFNN)and second-order sliding mode control(SOSMC)are employed for DFIG control.The aim is to enhance the power tracking capabilities of DFIG under sensor faults and uncertain conditions.Firstly,the control law of SOSMC is derived using the super-twisting algorithm,and the asymtotic stability of the control system is proven using Lyapunov's second theorem.Then the utilization of RLFNN is proposed to estimate uncertain components,with the control law and parameters of RLFNN to be trained online,enhancing the robustness of the system.Simulation results demonstrate that the proposed method enables DFIGs to maintain sensor faults,parameter variations,and external disturbances normal operation under achieving effective fault-tolerant control.
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