Robust adaptive fuzzy type-2 fast terminal sliding mode control of robot manipulators in attendance of actuator faults and payload variation

• Дата: 2025
• Автори: Rahali, H., Zeghlache, S., Cherif, B. D. E., Benyettou, L., Djerioui, A.
• Формат: Стаття
• Мова: English
• Опубліковано: National Technical University "Kharkiv Polytechnic Institute" and Аnatolii Pidhornyi Institute of Power Machines and Systems of NAS of Ukraine 2025
• Теми: robot manipulator; type-2 fuzzy system; fast terminal sliding mode control; adaptive control
• Онлайн доступ: http://eie.khpi.edu.ua/article/view/307034
• Назва журналу: Electrical Engineering & Electromechanics

Introduction. This study presents a robust control method for the path following problem of the PUMA560 robot. The technique is based on the Adaptive Fuzzy Type-2 Fast Terminal Sliding Mode Control (AFT2FTSMC) algorithm and is designed to handle actuator faults, uncertainties (such as payload change), and external disturbances. The aim of this study is to utilize the Fast Terminal Sliding Mode Control (FTSMC) approach in order to ensure effective compensation for faults and uncertainties, minimize tracking error, reduce the occurrence of chattering phenomena, and achieve rapid transient response. A novel adaptive fault tolerant Sliding Mode Control (SMC) approach is developed to address the challenges provided by uncertainties and actuator defects in real robotics tasks. Originality. The present work combined the AFT2FTSMC algorithm in order to give robust controllers for trajectory tracking of manipulator’s robot in presence parameters uncertainties, external disturbance, and faults. We use an adaptive fuzzy logic system to estimate the robot’s time-varying, nonlinear, and unfamiliar dynamics. A strong adaptive term is created to counteract actuator defects and approximation errors while also guaranteeing the convergence and stability of the entire robot control system. Novelty. The implemented controller effectively mitigates the chattering problem while maintaining the tracking precision and robustness of the system. The stability analysis has been conducted using the Lyapunov approach. Results. Numerical simulation and capability comparison with other control strategies show the effectiveness of the developed control algorithm. References 53, table 1, figures 8.