Optimization Of PID Parameters Of PMSM Based On Cauchy Mutation Particle Swarm Optimization Algorithm

Permanent Magnet Synchronous Motor PID control, in order to obtain PID control effect is improved, the need to modify the differential coefficient PID,proportional coefficient, integral coefficient three parameters. In industry, hotspot automation and control has been a PID optimization control, add some optimization algorithms in the PID can effectively improve the accuracy of the parameters and the optimization of time, so that the PID parameter optimization has become a hot nowadays research wherein the optimization method is more commonly used in permanent magnet synchronous motor PID control parameters, including law experts,ZN method and the simplex method. In recent years, the smart algorithm in the control system are increasingly common, PID controller was added neural network control algorithm method is gradually rising. Previous optimization methods are relatively simple, but these optimization methods have shortcomings, such as law expert knowledge based on experience, expert knowledge to constantly re-trimming and correction; ZN method flexibility is not high, and more than a predetermined amount. In the neural network algorithm, due to the optimization process of its argument is not simple, so that the algorithm converges long time to reduce the accuracy of the control system, the traditional particle swarm search for the optimal position for a long time, and is easy to fall into local optimization. At this time, in order to solve the PID parameters optimized for low degree of convergence in the control accuracy is not high, and falling into local optimization problems based on Cauchy mutation particle swarm optimization parameters PID controller is proposed.Cauchy mutation particle swarm algorithm is to use Cauchy mutation longer "tail" to make global optimal particle(gbest) jump to a better position to escape local optimization, optimal PID parameters principle, first constructed motor current loop function model PI vector control, and vector control model when the permanent magnet synchronous motor. Then, depending on the nature of the particle swarm algorithm, based on the band inertia weight particle swarm optimization, adding Cauchy mutation operator to obtain Cauchy mutation algorithms, vectors and then permanent magnet synchronous motor speed control system based on added Ke West mutation particle swarm optimization controller PID parameters, the simulation algorithm. Experiments show that, based on Cauchy mutation particle swarm optimization magnet synchronous motors PID number optimization of searchcapability, high search ability, good stability, good dynamic performance advantages.