Trajectory Tracking of a Mobile Robot with GWO-Based Type-II Fuzzy Logic Controller

Year 2025, Volume: 14 Issue: 4, 1523 - 1551, 31.12.2025

Tayfun Abut , Enver Salkım

https://doi.org/10.17798/bitlisfen.1753970

Abstract

This study addresses the trajectory tracking problem of wheeled mobile robots and proposes two different control strategies, which are comparatively evaluated through simulations. Initially, the mathematical model of the mobile robot is derived, followed by the design of two controllers: a conventional Proportional-Integral-Derivative (PID) controller and a Type-II Fuzzy Logic Controller (Type-II FLC) optimized utilizing the Grey Wolf Optimizer (GWO) algorithm. The suggested control methods are assessed under three different reference trajectory scenarios—circle, square, and star-shaped paths. Simulation results indicate that the PID controller exhibits significant deviations, particularly during sharp turns and sudden maneuvers in square and star trajectories, leading to increased tracking errors. In contrast, the GWO-based Type-II FLC demonstrates smoother and more stable maneuvers, resulting in lower tracking errors and higher trajectory-following accuracy. These findings suggest that the GWO-optimized Type-II FLC enables more reliable and precise navigation of mobile robots in dynamic environments contrasted to the classical PID controller. Furthermore, the Type-II FLC method achieved considerable percentage improvements in tracking performance for circular, square, and star trajectories when contrasted with the PID controller. Specifically, in a square orbit, the X and Y position errors have been improved by 98% and 97%, respectively, according to the Type II FLC, PID control method. Overall, the results highlight the effectiveness of the suggested control method in enhancing position control accuracy.

Keywords

Mobile Robot , Type II Fuzzy Logic Control , PID Controller , Grey Wolf Optimization Algorithm

Ethical Statement

This article does not contain any studies with human participants or animals performed by any of the authors.

Supporting Institution

This work was supported by Muş Alparslan University Scientific Research Coordination Unit Project Number, as a project numbered BAP-24-MMF-4901- 03.

Project Number

BAP-24-MMF-4901- 03

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