A control strategy based on intelligent algorithm (PSO) to perform electrical stimulation systems

Abdennacer Ben Hmed (1, 2) , Toufik Bakir (2) , Anis Sakly (1) , Stéphane Binczak (1)

1 Le2i - Laboratoire d'Electronique, d'Informatique et d'Image [EA 7508]
2 ESIER - Unité Etudes des Systèmes Industrielles et des Energies Renouvelables

Adjusting stimulation parameters using control strategy based on reliable mathematical model that can predict perfectly the muscle response, may improve the efficiency of Functional Electrical Stimulation (FES) systems. In the present project, we investigate the PID control tuning based on the Particle Swarm Optimization (PSO) algorithm at the first time in neuro-muscular systems for updating automatically the stimulation pulse amplitude to track a desired force profiles. In the beginning, The PSO algorithm is used to identify unknown force model parameters. Next, optimal PID gains are found by the same intelligent algorithm to improve the control system. The obtained results showed promise in application of intelligent algorithm tuning PID methods in FES systems.

Mots clés: muscle force model; PID controller; PSO algorithm; Functional Electrical Stimulation; pulse amplitude.

Domaines: Automatique / Robotique

Abdennacer Ben Hmed, Toufik Bakir, Anis Sakly, Stéphane Binczak. A control strategy based on intelligent algorithm (PSO) to perform electrical stimulation systems. Journées d'Etude sur la TéléSANté, 6ème edition, Pôle Capteurs, Université d'Orléans, May 2017, Bourges, France. ⟨hal-01692459⟩