Particle swarm optimisation (PSO)-based controller strategies for energy efficient PMDC motor drives

摘要

The paper presents the application of particle swarm optimisation (PSO) technique for online tuning of error-driven self-adjusting multi-loop dynamic speed regulators for large industrial PMDC motor drives. Novel multi-loop dynamic error regulator include Tan-sigmoid controller, multi-zone controller and incremental self-regulating controllers are developed by the first author using multi-objective particle swarm optimisation (MOPSO) for high performance efficient PMDC motor drives. The three novel dynamic efficient control schemes utilise speed, current, dynamic momentum excursion error and limited current ripple errors as main inputs to vary the firing delay angle a of the 6-pulse controlled thyristor rectifier. The tuning selection criterion for optimal control gains is based on effective robust dynamic tracking of selected speed reference trajectories. The optimisation process is based on minimising the system control total error, the steady state error, settling time, rising time, and maximum overshoot.