Fuzzy rule base optimization of fuzzy controller using Hybrid Tabu Search and Particle Swarm Optimization learning algorithm

In this paper, Hybrid Tabu Search (TS) and Particle Swarm Optimization (PSO) is proposed to generate Fuzzy Controller with only three rules. The algorithm dynamically adjusts the membership functions and fuzzy rules according to different environments. At each iteration of PSO algorithm, we calculate the best solution and we seek the best neighbor by Tabu search, this operation minimizes the number of iterations and computation time while maintaining accuracy and minimum response time. The algorithm was tested on the control of angle of inverted pendulum.