Fast Hybrid PSO and Tabu Search Approach for Optimization of a Fuzzy Controller

TL;DR

This paper presents a hybrid PSO and Tabu Search method to efficiently optimize a Takagi-Sugeno zero-order fuzzy controller, improving response time and reducing computation for controlling an inverted pendulum.

Contribution

The paper introduces a novel hybrid optimization algorithm combining PSO and Tabu Search for tuning fuzzy controllers, reducing iterations and computation time.

Findings

Optimized fuzzy controller for inverted pendulum achieved faster response.

Hybrid method reduced optimization iterations and computation time.

Maintained accuracy and stability in control performance.

Abstract

In this paper, a fuzzy controller type Takagi_Sugeno zero order is optimized by the method of hybrid Particle Swarm Optimization (PSO) and Tabu Search (TS). The algorithm automatically adjusts the membership functions of fuzzy controller inputs and the conclusions of fuzzy rules. At each iteration of PSO, 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. We apply this algorithm to optimize a fuzzy controller for a simple inverted pendulum with three rules.