Robust Control Design Procedure Based on Particle Swarm Optimization and Kharitonov’s Theorem with an Application for PMSMs

Abstract

This paper proposes an automatic procedure for robust control design applicable to power converters based on particle swarm optimization and Kharitonov's Theorem. The main benefit is to provide control gains that have a theoretical certificate of robust stability and also accomplish multiple performance criteria in a design less dependent of human-machine interaction. Regarding the particle swarm optimization, each particle represents a controller candidate whose performance is evaluated by means of an objective function, using the vertices of a polytopic model of the plant and the four polynomials of Kharitonov's Theorem. The effectiveness of the proposed procedure is illustrated by means of a case study that considers the speed control of a permanent magnet synchronous motor subject to uncertain mechanical and electrical parameters. The designed controllers, obtained in an offline way, yield good trade-offs between performance and robustness, as confirmed by simulation and experimental evaluations. Analyses show superior results with the proposed strategy compared to a genetic algorithm and to a design tool specialized for PID tuning, indicating its viability as an alternative for robust control design in power electronics.

Melhoria De Desempenho De Motores De Relutância Variável Via Algoritmo De Enxame De Partículas

“…A análise, no entanto, não foi estendida para motores. Uma alternativa para problemas com difícil formulação analítica é o uso de algoritmos inteligentes, como o algoritmo de otimização por enxame de partículas (do inglês, Particle Swarm Optimization -PSO) [20], [21]. Na literatura verifica-se utilização do PSO aplicado a otimização de projeto de SRMs, como [22], [23].…”