Robust and Intelligent Fuzzy Logic Controllers for a Differential Mobile Robot Trajectory Tracking

This paper presents an investigation and a design of efficient type-1 and type-2 fuzzy logic controllers for differential drive trajectory tracking in mobile robotics. The objective is to propose a control structure based on human expert knowledge that can steer a mobile robot along a desired path with minimal errors, leveraging the advantages of fuzzy logic systems. The study focuses on analyzing the impact of the fuzzy controller structure and parameters on the quality of path-tracking performance. Two distinct fuzzy systems, one type-1, and one type-2, are conceived and simulated for this task. The controllers are tested and evaluated through simulations involving various trajectory types to demonstrate their efficiency and robustness in trajectory tracking. A comprehensive performance comparison between the two fuzzy controllers is conducted by analyzing their respective behaviors across multiple path scenarios. The obtained simulation results indicate that the type-2 fuzzy logic controller exhibits superior capabilities in accomplishing the trajectory tracking task, outperforming the type-1 fuzzy logic controller. The type-2 fuzzy logic controller demonstrates improved performance and robustness, enabling more accurate and reliable path tracking for mobile robots.