Research on Multi-motor Cooperative Control Method Based on Hybrid Particle Swarm Algorith

In this paper, the cooperative control of multiple brushless DC motors is investigated, and an improved ring-coupled control structure is designed, and an intelligent PID control algorithm is studied based on this structure to realise the high-precision cooperative control of multi-motor systems. A hybrid particle swarm algorithm is proposed to optimise the fuzzy rules of the fuzzy PID algorithm, so as to achieve the automatic optimisation of the controller parameters and improve the synergy of the multi-motor control system. In order to improve the convergence accuracy of the algorithm, after the particle swarm algorithm determines the individual historical optimal value and the global optimal value, a natural selection algorithm is inserted to rank the particles according to the size of the fitness value calculated by the fitness function, replace the poorly adapted particles, but keep the historical optimal value of these particles, increase the diversity of the algorithm population, and help the algorithm escape from the local optimal solution more quickly. The results show that the proposed algorithm can effectively improve the stability, reliability, and cooperative ability of the multi-motor control system, which provides a reference for the application of intelligent control algorithms in the multi-motor cooperative control system.