Research on brushless DC motor control based on multi-strategy fusion algorithm
In order to solve the problem that it was difficult to formulate fuzzy rules in complex situations,based on the sand cat swarm algorithm,the algorithm was optimized by integrating Gaussian random walk strategy,the alert mechanism of Sparrow algorithm and the chaotic mapping.The test showed that the multi-strategy algorithm was superior to the comparison algorithm.Decimal encoding were carried out to fuzzy rules to realize iterative optimization of the algorithm.This optimization method was used in the brushless DC motor speed control system and simulation experiments were conducted.The results proved that the fuzzy PID control after optimizing the fuzzy rules had better control performance,verifying the efficacy of the proposed fuzzy rule optimization method.
fuzzy rule optimizationimprove the sand cat swarm algorithmbrushless DC motorchaos mappingGaussian random walk strategy
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