Closed Loop Nonlinear Model Predictive Control Applied On Paralyzed Muscles To Restore Lower Limbs Functions

The main goal when applying functional electrical stimulation (FES) to the paralyzed lower limbs of the paraplegic patients is to avoid hyperstimulation and to defer the muscular fatigue as much as possible. In this paper a closed loop position control of the knee joint actuated by the quadriceps muscle to perform flexion-extension has been presented. The feedback control consists of a model predictive control (MPC) technique which is also known by a receding horizon control or moving horizon control. This controller is applied to a complex physio-mathematical muscle model that is based on a macroscopic Hill and a microscopic Huxley concepts. An MPC constitutes an adequate controller with nonlinear multivariable systems. Furthermore it enables us to incorporate explicitly constraints on inputs, outputs and system states. The controller has shown a robustness against force perturbation and model mismatch as well as high capability of tracking a pre-defined reference trajectory