Study on Iterative Learning Control of Elbow Movement Based on Functional Electrical Stimulation
Functional electrical stimulation(FES)is an important method for treating post-stroke movement disorders.Considering that the existing kinetic modeling methods are complicated and the control accuracy needs to be im-proved,this paper proposes an iterative learning control method with a forgetting factor for elbow movement based on FES.This research utilizes the Hammerstein structure to establish the musculoskeletal model of the elbow,on the ba-sis of which the FES system with iterative learning control with forgetting factor is designed.The reliability of the established musculoskeletal model is examined by calculating the root-mean-square error and the maximum angular error between the actual output of the sample and the output angle of the model.The control effect of the closed-loop FES system is evaluated through simulation analysis and actual control experiments,and compared with the tradi-tional iterative learning control FES system to illustrate the effectiveness of the control method.The results show that the established musculoskeletal model of the elbow is suitable for studying the kinematic characteristics of the elbow joint under electrical stimulation,and that the iterative learning control method with a forgetting factor exhibits supe-rior performance in elbow control.