Particle swarm optimization-optimized integrator backstepping for the control of electric wheelchairs velocity

Particle swarm optimization-optimized integrator backstepping for the control of electric wheelchairs velocity

Electric powered wheelchair
Integrator backstepping control
Optimization
Particle swarm optimization
Permanent magnet synchronous motors

Most people suffering from temporary or permanent disabilities rely on wheelchairs or electric powered wheelchairs (EPW) to maintain autonomy of movement. To address different EPW control challenges, several studies have investigated this kind of robot. This paper focuses on the optimization of the integrator backstepping control parameters of the EPW. The system operates using two permanent magnet synchronous motors (PMSM), noted for their great efficiency, substantial torque, minimal noise, and robustness. At first, the dynamic model for both EPW-motors is showned. After that, a nonlinear integrator backstepping command based on Lyapunov’s second technique, which combines the choice of the energy function with the control laws, was applied to the resulting global model. To ensure optimal performance, the control parameters were tuned by means of an optimization approach. Specifically, the particle swarm optimization technique (PSO) was employed to search for the optimal parameters (gains) of the integrator backstepping controller. In order to assess the performance of the optimized backstepping–based control approach, numerical simulations were conducted to illustrate the evolution of both electrical and mechanical velocity- related variables.

Djamila Boubekeur1,2, Khayreddine Saidi3,4, Mohammed Messirdi3, Abdelmadjid Boumédiène3

Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA

Oct 19, 2025

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