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Because of the control method of permanent magnet motor in a lower limb rehabilitation equipment, the research is carried out based on the CSBP Neural Network to Optimize PID Controller Parameters for better control performance of the motor to obtain a more stable control process. From the characteristics of lower limb rehabilitation training can be seen that the speed loop proportional integral (PID) control model is introduced and by using the CSBP neural network the parameters of Kp, Ki, Kd of the PID controller are optimized, which process are carried out calculation under the MATLAB/Simulink. The results show that the output curves of the PID controller after CSBP, which concluded that the optimized controller model could quickly and adaptively adjust PID parameters, and the control effect is obviously better than traditional PID controller.
Inspec keywords: neurocontrollers; optimal control; permanent magnet motors; patient rehabilitation; three-term control; fuzzy control
Subjects: Optimal control; Fuzzy control; Biological and medical control systems; Control of electric power systems; Neurocontrol; Spatial variables control; d.c. machines