Identification of black-box nonlinear models for lower limb movement control using functional electrical stimulation

In this work, the problem of identification of nonlinear models for the functional electrical stimulation (FES) process is considered. In particular, experiments of stimulation of the quadriceps muscle group and the subsequent movement (or torque release) of the knee-joint will be examined. Both isometric and isotonic experimental conditions are described and NARX models will be identified from data, considering polynomial and neural network structures. For both model families, the issues of parameter estimation, structural identification and model validation will be discussed and effective solutions are proposed.