Control and estimation for the design of a smart electrostimulator using Ding et al. model

Abstract

Based on the A. V Hill’s muscle model (Medicine Nobel prize 1922), mathematical models validated by experiments due to Ding et al. in the 2000’s allow to describe the muscular force isometrical contraction due to electrostimulation, taking into account the fatigue. They serve as a model to control and to predict the effect of trains of electrical stimulations, with rest periods aiming to force rehabilitation or reinforcement. In this article we briefly present the main issues of the problem. Two typical training sessions are described related to increase the force or the endurance. Each program is translated into an optimization problem which is analyzed in the sample-data control frame. The parameters of the models split into parameters independent of each individual vs. parameters related mainly to the fatigue, which have to be online estimated. Geometric estimation theory leads to describe a software sensor to make explicit computations. NMPC algorithm vs MPC algorithm can be used to regulate the force.