Tuning of FP-PID Controller based on PSO Algorithm Applied to a Human Gait

• Rodrigo B. de Medeiros UnB
• Daniel M. Muñoz UnB

Resumo

Robotic manipulators are multi-input multi-output (MIMO) systems with nonlinear points affected by numerous uncertainties and disturbances. PID controllers are widely used in industry for kinematic and dynamic control. However, when applied to MIMO systems, they are not easy to tune and require performance improvements. In this work, a PID controller is proposed with a fuzzy precompensator (FP-PID), both tuned by the bioinspired particle swarm optimization (PSO) algorithm to a two-degree of freedom (2-DOF) robotic manipulator representing a human leg. To validate the system, two real datasets of human gait were used: normal walking and stair climbing to estimate the error trajectory of the manipulator. The statistical analysis of the PSO algorithm with 16 experiments was satisfactory, and the addition of the fuzzy precompensator to the conventional PID resulted in a reduction of the mean square error of one of the manipulator links by up to 73 percent.

Palavras-chave: Legged locomotion, Uncertainty, Statistical analysis, Service robots, Stairs, Trajectory, Robots, Fuzzy precompensated PID controller, Fuzzy logic controller, 2-DOF Robotic manipulator, PSO, Human Gait