Design of Fuzzy Controller rule base using Bat Algorithm

Abstract

The work in this paper revolves fundamentally around the main axes of fuzzy control of the type Takagi-Sugeno (T-S) zero order for dynamic, complex nonlinear systems. In this paper, we present method for designing Fuzzy controller rule base using a new swarm intelligence algorithm, which is based on the Bat algorithm. The Bat algorithm is one of the most recent swarm intelligence based algorithms that simulates the intelligent hunting behavior of the bats found in nature. The main objective is to design the fuzzy rule base of fuzzy controller respecting the desired performance. To demonstrate the efficiency of the suggested approach, a control of a Magnetic Ball Suspension System is selected. Simulation results shows that the proposed approach could be employed as a simple and effective optimization method for achieving optimum determination of fuzzy rule base parameters.