Design of a Fuzzy Logic Controller by Ant Colony Algorithm with Application to an Inverted Pendulum System

Fuzzy logic controller is one of the most important applications of fuzzy-rule-based system that models the human decision processing with a collection of fuzzy rules. Choosing appropriate fuzzy rules and sets is essential for a fuzzy Logic controller to perform at the desired level. In this paper, an adaptive ant colony algorithm is proposed based on dynamically adjusting the strategy of selection of the paths and the strategy of the trail information updating. The algorithm is used to design a fuzzy logic controller automatically for real-time control of an inverted pendulum. In order to avoid the combinatorial explosion of fuzzy rules due to multivariable inputs, state variable synthesis scheme is employed to reduce the number of fuzzy rules greatly. The simulation results show that the designed controller can control the inverted pendulum successfully.

I. Introduction

Since Zadeh first introduced the fuzzy set theory, there has been a rapid growth in the applications of fuzzy logic. Fuzzy Logic controller is one of the most popular applications. It models the human decision processing with fuzzy linguistic variables, and converts the experience of skilled operators into a set of fuzzy control rules. Since the fuzzy rules and the fuzzy sets used in the rules play a crucial role in the performances of fuzzy Logic controller, choosing the right rules and fuzzy sets becomes an important issue [1].