Title: Design of MIMO fractional order fault tolerant control based on intelligent QFT controller of robotic manipulator

Authors: Najah Yousfi-Allagui; Asma Aribi; Awad M. Aljuaid

Addresses: College of Engineering, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia; Control and Energy Management Laboratory (CEM), Engineering School, University of Sfax, BP W, 3038 Sfax, Tunisia ' Department of Electrical Engineering, College of Engineering, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia; Research Unit of Modeling, Analysis and Control of Systems, National Engineering School of Gabes, University of Gabes, MACS 06/UR/11-12, Tunisia ' College of Engineering, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia

Abstract: Control systems that ensure safety, reliability and maintainability are challenging tasks to remedy the problems caused by unexpected faults. The quantitative-feedback-theory is efficient control method used for MIMO-systems with parametric uncertainties. Besides, the robust fractional-PID controller and fractional pre-filter demonstrated their efficiency to ensure robust control and performance specifications. The novelty consists of associating the benefits of fractional control and the QFT approach to develop a fractional-tolerant-controller for MIMO systems. A fractional fault-tolerant controller (FFTC) with some special characteristics allowing to overcome the design complexity and control effort increase due to simultaneous presence of disturbance with jumping faults is developed. Additionally, high-tracking performance is taken into consideration. The proposed approach is designing a controller with structure that converts the faults and the interaction in MIMO system to standard QFT disturbance rejection problem and guarantees high performance thanks to fractional approach. The proposed approach is applied to SCARA robot manipulator.

Keywords: evolutionary algorithms; fault tolerant control; FTC; fractional control; multi-criteria optimisation; quantitative feedback theory; QFT; robotic systems.

DOI: 10.1504/IJMIC.2024.139098

International Journal of Modelling, Identification and Control, 2024 Vol.44 No.4, pp.303 - 314

Received: 31 Oct 2022
Accepted: 07 Mar 2023
Published online: 13 Jun 2024 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article