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.