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In this paper, a radial basis neural network adaptive sliding mode controller (RBF-NN ASMC) for nonlinear electromechanical actuator systems is proposed. The radial basis function neural network (RBF-NN) control algorithm is used to compensate for the friction disturbance torque in the electromechanical actuator system. An adaptive law was used to adjust the weights of the neural network to achieve real-time compensation of friction. The sliding mode controller is designed to suppress the model uncertainty and external disturbance effects
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