Fuzzy Self-tuning PID Control Method Based on Multi Intelligent Particle Swarm Optimization Algorithm

DC speed regulating system is a complex control system with degradation and nonlinearities, and difficult to establish a precise mathematical model. The traditional control methods depend on accurate mathematical modelling of the controlled object, and it is not possible to dynamically adapt to the DC speed control system to obtain high control precision. An improved hybrid genetic algorithm for PID is proposed to deal with the big randomness of slow iteration process, weak local searching capacity and other problems in harmonic detection simulation with genetic algorithms. The method i) improves the complexity of the genetic algorithm, ii) enhances its calculation efficiency with strong local convergence capacity of quasi-Newton algorithm, and iii) solves such problems as insufficiently precise harmonic balance simulation and slow operation in practical condition. Our simulation results show that the algorithm has such advantages of: i) less number of iterations, ii) fast convergence rate, iii) high convergence efficiency, iv) high solution precision, and v) can significantly improve calculation efficiency for solving harmonic detection equations. In addition, the simulation and measured curves fit well to explain: i) insufficiently precise simulation results, ii) slow operation and other problems, and has promising application prospects.