Abstract
The main contributions of this thesis concern the modelling and the identification of the<br />skeletal muscles under Functional Electrical Stimulation for the rehabilitation of the paralysed limbs.<br />There are two objectives of modelling: 1) the simulation and the synthesis of the movement, to<br />evaluate the performances of the system a priori and, 2) to test and validate the control schemes based<br />on the referred control model such as the adaptive control or predictive control.<br />The muscle model proposed is an original multi-scale model presented in the state space with a set of<br />differential equations where the input is an electrical signal provided by electrical stimulator such as<br />the "PROSTIM" offering the possibility of tuning the amplitude, the pulse width and the frequency of<br />the electrical signal of stimulation, and the outputs are the muscle force and stiffness. The model<br />proposed integrates the macroscopic (muscle scale) and microscopic (fibre scale) dynamic behaviour of<br />the muscle with two control input, a "static" input for the rate of recruitment and a "chemical" input.<br />The parameters of this model were identified experimentally in isometric mode on animal with classical<br />techniques of identification such as Levenberg-Marquardt and the Extended Kalman Filter. The cross<br />validations illustrate the pertinence of the model and the quality of the estimate.