Hybrid integral sliding mode and fuzzy logic control for omnidirectional robots: modified elephant herding optimization for trajectory tracking

Abstract

Trajectory tracking and robust motion control remain central challenges in autonomous robotic systems operating under nonlinear and uncertain conditions. This study proposes a novel hybrid control framework that integrates Integral Sliding Mode Control (ISMC), whose control parameters are calculated using a Sugeno-type Fuzzy Logic Controller (FLC) and a Modified Elephant Herding Optimization (MEHO) algorithm. The approach is implemented on a three-wheeled omnidirectional mobile robot (TOMR), with detailed dynamic and kinematic modeling. The MEHO algorithm enhances exploration–exploitation balance and accelerates convergence through adaptive update mechanisms. To assess the performance of the proposed controller, a triangle and C-shape trajectories are implemented. Simulation results using MATLAB R2022b show that the proposed system reduces positional errors in the X and Y axes to below 0.005 m, and orientation error to 0.0014 rad within 2 s. The root mean square errors (RMSE) for X, Y, and orientation for the triangle trajectory are 3.48 × 10⁻⁵ m, 2.51 × 10⁻⁶ m, and 0.00287 rad, respectively and for the C-shape trajectory are 6.538*10− 6 m, 2.614*10− 6 m, and 1.051*10− 5 rad for X, Y, and orientation, respectively. Compared to classical EHO-based and adaptive neural sliding controllers, the proposed method achieves up to 50% lower torque variation and over 60% faster settling time. The modular and learning-based design enables generalization to other robotic platforms, including aerial robots operating in uncertain or dynamic environments.