Optimal Control of Non-Holonomic Robotic Systems Based on Type-3 Fuzzy Model

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.

Keywords

• Adaptive control
• fuzzy control
• non-holonomic
• optimal control
• robotic systems
• symmetrical constraints