Novel particle swarm optimisation (PSO) self regulating control schemes for dynamic error driven PMDC motor drives

Abstract

The paper presents a number of novel applications of particle swarm optimisation (PSO) for optimal tuning of controller parameters for high performance permanent magnet PMDC industrial motor drives. The new proposed control schemes based PSO will ensure smooth starting torque, enhance acceleration and dynamic tracking of reference speed trajectory under different loading conditions and parametric variations. The dynamic simulation results are shown for both single objective particle swarm optimisation (SOPSO) and the multi objective particle swarm optimisation (MOPSO). This paper presents a new tuning and self regulating control algorithm for finding the set of trade-off optimal controller gains based on MOPSO. In MOPSO, the objectives are all essential but some are in conflict with each others. In this case, the optimality is not a single point, but an optimality surface where the operator can select its desired trade-off operating point.