Optimal Control of Non-Holonomic Robotic Systems Based on Type-3 Fuzzy Model
Lili Wu, Haiyan Huang, Meng Wang, Khalid A. Alattas, Ardashir Mohammadzadeh, Ebrahim Ghaderpour
Abstract
The paper studies the control of wheeled land mobile robots (MRs) using nonlinear equations and non-holonomic dynamic constraints. Due to the complex and unpredictable nature of the environments in which these robots operate, designing a controller for them is a challenging task. Uncertainties in the system further compound the problem. To tackle these challenges, this paper proposes a novel approach based on type-3 (T3) fuzzy logic systems (FLSs) for system identification and parameter estimation. The T3-FLSs are used to create an online model of the MRs dynamics, which is then used to design a model-based control system. To account for the approximation error of T3-FLSs and the effect of un-modeled dynamics and constraints, an optimal supervisor is designed. The supervisor compensates for any error in the model and ensures that the control system remains stable under symmetrical constraints. A Lyapunov analysis is conducted to verify the stability of the system. The simulations demonstrate that the proposed controller yields excellent results even in the presence of non-holonomic constraints and fully unknown dynamics. The findings of this study offer significant insights into the challenges associated with controlling MRs and provide a promising solution to address these issues.