Adaptive Control of a DC Motor Based on Swarm Intelligence

The effect of uncertainties in the stabilization of the velocity control of a DC motor is compensated by proposing an adaptive control based on Particle Swarm Optimization (ACPSO). The ACPSO is based on an on-line dynamic optimization problem with dynamic constraints. The empirical analysis based on modifying the inertia weight of the ACPSO indicates that it can effectively regulate the motor´s velocity and hence the ACPSO can be another alternative to control the DC motor under parametric uncertainties. Simulation results verify the proposed approach.