Robust adaptive fuzzy sliding mode control for trajectory tracking for of cylindrical manipulator

Pham, Van Cuong, Tran, Minh Hai, Nguyen, Phuc Anh, Vu, Ngoc Son, Thi, Nga Nguyen

arXiv.org Artificial Intelligence 

Abstract: This research proposes a robust adaptive fuzzy sliding mode control (AFSMC) approach to enhance the trajectory tracking performance of cylindrical robotic manipulators, extensively utilized in applications such as CNC and 3D printing. The proposed approach integrates fuzzy logic with sliding mode control (SMC) to bolster adaptability and robustness, with fuzzy logic approximating the uncertain dynamics of the system, while SMC ensures strong performance. Simulation results in MATLAB/Simulink demonstrate that AFSMC significantly improves trajectory tracking accuracy, stability, and disturbance rejection compared to traditional methods. This research underscores the effectiveness of AFSMC in controlling robotic manipulators, contributing to enhanced precision in industrial robotic applications. Keywords: Adaptive Fuzzy Sliding Mode Control (AFSMC), Sliding Mode Control (SMC), Fuzzy Logic, Robotic Manipulators, Cylindrical Manipulator 1. INTRODUCTION Cylindrical robotic manipulators, combining a prismatic and a revolute joint, are extensively utilized in applications such as CNC machining, 3D printing, and assembly tasks.