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

TL;DR

This paper introduces a robust adaptive fuzzy sliding mode control method that combines fuzzy logic and sliding mode control to improve trajectory tracking, robustness, and disturbance rejection in cylindrical robotic manipulators, with demonstrated simulation success.

Contribution

It presents a novel AFSMC approach integrating fuzzy logic with sliding mode control for enhanced robotic manipulator performance.

Findings

Significant improvement in trajectory tracking accuracy.

Enhanced stability and disturbance rejection.

Effective control demonstrated through MATLAB/Simulink simulations.

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.