Fuzzy Predictive Controller for Trajectory Tracking of Differential-Drive Mobile Robot

Abstract

The aim of this paper is to develop a fuzzy predictive control approach for nonholonomic mobile robots. To achieve this objective, we introduce an innovative strategy to address specific challenges that emerge when utilizing linear models for nonholonomic mobile robots. The approach employed involves extending the error model through the integration of a Takagi-Sugeno fuzzy logic system. By considering various values of dynamic behavior, multiple linear error models are derived, providing the groundwork for formulating the T-S fuzzy model. Importantly, the resulting fuzzy model maintains alignment with the original model while simultaneously enhancing its precision. The practical effectiveness of our proposed methodology is demonstrated through its application in guiding a nonholonomic mobile robot along a predefined reference path within two distinct tracking scenarios.