Controle dinâmico de um punho para prótese transradial usando controlador PID, Lógica Fuzzy e otimização por enxame de partículas

Abstract

This study presents the development of a hybrid intelligent control system for a transradial prosthetic wrist, integrating Proportional-Integral-Derivative (PID) control, Fuzzy Logic, and Particle Swarm Optimization (PSO). The prosthesis, designed by Labbio, incorporates a motor, harmonic reducer, and magnetorheological (MR) brake to enable precise torque control. Three distinct operation scenarios were considered: abrupt motion, smooth high-precision movement, and a hybrid mode alternating between both. A mathematical model of the wrist mechanism was formulated, relating motor and brake electrical inputs to the output torque while respecting mechanical constraints. For each scenario, torque reference curves were defined, and PID parameters were automatically optimized using PSO. To enable real-time adaptability, a Fuzzy Logic system dynamically selects the most appropriate PID gains based on the movement regime. Simulation results demonstrate that the hybrid control system achieves stable and responsive performance across all scenarios. The Fuzzy-PSO-PID approach enables smooth transitions between motion types, reducing overshoot and delay while enhancing precision and user comfort. This work highlights the potential of combining classical control, soft computing, and bio-inspired optimization techniques to address nonlinear and time-varying challenges in biomedical prosthetic applications.