Adaptive Sliding Mode Neural Network Control Based on Improved Dung Beetle Optimization
In order to solve the problems of jitter and low parameter adaptability and the challenge of uncertain dis-turbance in the sliding mode controller in the mobile robot tracking system,an adaptive sliding mode neural network control method based on improved dung beetle optimization is proposed.A sliding mode controller based on combinatorial approach law and adaptive radial basis function(RBF)neural network is used to solve the problems of jitter and uncertain disturbance of the system,which solves the jitter problem of the system and the influence of external interference on the system,and re-alizes the accurate tracking of the desired trajectory of the mobile robot.Based on this controller,an improved dung beetle optimization algorithm is introduced to optimize the controller parameters,which enhances the adaptability of the controller parameters and improves the stability of the system.Based on the simulation results,the proposed method can not only ena-ble the mobile robot to track the expected trajectory quickly and accurately,but also effectively overcome the influence of uncertain interference on the system.The research results can be applied to the fields of motion control and optimization of mobile robots.
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