A modified Active Disturbance Rejection Controller(ADRC)is designed to address the issue of various nonlinear dis-turbances affecting the response speed and tracking accuracy of a certain obstacle breaking weapon position servo system during opera-tion.By utilizing the advantages of good adaptability and self-learning ability of BP neural network(BPNN),the relevant parameters of ADRC are optimized online,and the artificial fish swarm algorithm(AFSA)is used to optimize the weights of the neural network,in order to further improve the performance of the controller.Using MATLAB software to simulate and verify the controller,the simu-lation results show that this control method can improve the anti-interference ability and tracking accuracy of the servo system.
关键词
随动系统/破障武器/BP神经网络/人工鱼群算法/自抗扰控制
Key words
servo system/barrier breaking weapon/BP neural network/artificial fish swarm algorithm/ADRC
维普
万方数据