Genetic Feedforward-Feedback Controller for Functional Electrical Stimulation Control of Elbow Joint Angle

Background: Functional electrical stimulation (FES) is the most commonly used system for restoring functions after spinal cord injury (SCI). Objective: In this study we investigated feedback PID and feedforward-feedback P-PID controllers for regulating the elbow joint angle. Methods: The controllers were tuned based on a nonlinear muculoskeletal model containing two links, one joint with one degree of freedom and two muscles in the sagittal plane that was simulated in MATLAB using Sim Mechanics and Simulink toolboxes. The first tune of the PID and P-PID controllers was done by trial and error. Then, the coefficients were optimized by genetic algorithm (GA). For checking the robustness of the controllers, we compared the amount of rise time, settling time, maximum overshoot and steady state error under three conditions: the first was when the initial angle of the joint was fixed and only the desired angles changed; the second was with a fixed step as input and various initial angles; and the last condition was with different maximum forces for muscle. Results: Genetic controllers had better performance than the trial and error tuned controllers. The amounts of settling time were not so different for the controllers in condition 1 but had more variations in condition 2 and had really better results in genetic P-PID in condition 3. The overshoot was pretty less in PIDs than in P-PIDs and the steady state error was almost zero for all of the controllers. Conclusion: Genetic controllers had a better performance than the trial and error tuned controllers. The rise time was much less in P-PIDs than in PIDs.