Fault Detection & Fault-Tolerant Control of Permanent Magnet Linear Motors

Associated with: Murdoch University

Duration: Jul 2024 – Dec 2025

Remote research collaboration with Murdoch University focused on enhancing reliability and performance of Permanent Magnet Linear Motors (PMLM) under real-world uncertainties. Developed an integrated control architecture combining an Emotional Learning-Based Neural Network (ELBNN) with a Linear Extended State Observer (LESO) to detect and compensate for system faults.

Skills: MATLAB Programming, Simulink, Control Systems, Neural Networks, Fault Detection, Fault-Tolerant Control

Key Contributions:

• Designed fault detection mechanism using ELBNN
• Implemented Linear Extended State Observer for disturbance estimation
• Validated approach on PMLM systems under various fault conditions

Publication:

• Fault Detection and Fault-Tolerant Control of Permanent Magnet Linear Motors Using an Emotional Learning-Based Neural Network and a Linear Extended State Observer - Murdoch University