Design of Digital System Identification Controller for a Nonlinear Knee Model in Closed-Loop Functional Electrical Stimulator (FES)

Functional Electrical Stimulation (FES) devices represent a valuable rehabilitation intervention for patients with spinal cord injury (SCI). SCI can result in significant functional impairments, including the loss of movement in the lower body. Currently, closed-loop stimulation strategies are preferred over open-loop systems, as the latter’s trial-and-error approach can lead to premature muscle fatigue. However, while closed-loop systems offer promise, feedback controllers often exhibit inadequate performance when addressing nonlinear effects in knee muscles, such as stiffness, spasticity, and fatigue. To address these challenges, an adaptive feedback controller equipped with a system identification controller is crucial for accurately detecting these nonlinear parameters in knee muscles. This paper proposes the development of a digital system identification controller designed to detect nonlinear parameters from the knee extension model’s response. The system identification was implemented and simulated using hardware description language (HDL) Verilog code, with its performance evaluated through HDL co-simulation in MATLAB Simulink. The simulation results indicate that all nonlinear effects including stiffness, spasticity and fatigue are identifiable once the rate-of-change response stabilizes at 4 s.