Parameters Optimization of Fuzzy Controller Based on Improved Particle Swarm Optimization

The Particle Swarm Optimization technique (PSO), which refines its search by attracting the particles to positions with good solutions, has ever since turned out to be a competitor in the field of numerical optimization. The PSO can generate high-quality solutions within shorter computation time and have more stable convergence characteristic than other stochastic methods. In this article, Improved Particle Swarm Optimization is used to tune the parameters of fuzzy-PID controller. A new method to estimate scaling factors of the fuzzy PID controller for the inverted pendulum is investigated. The performance of the fuzzy PID controller is sensitive to the variety of scaling factors. The design procedure dwells on the use of particle swarm optimization and estimate algorithm. The tuning of the scaling factors of the fuzzy PID controller is essential to the entire optimization process. And the scaling factors of the fuzzy PID controller is estimated by means of regression polynomials. Numerical studies verify the effectiveness.