Muhammad A. Alsubaie
University of Southampton, Public Authority for Applied Education and Training
Papers
6
Total Citations
49
H-Index
4
About
Muhammad A. Alsubaie is a control systems researcher whose work focuses on the theory and application of iterative learning control (ILC) and repetitive control (RC). His major contributions lie in unifying the design frameworks for these two powerful control strategies, demonstrating that they share a common structure differentiated only by the placement of an internal disturbance model. This insight, detailed in his most-cited paper (20 citations), enables the transfer of controller designs between domains and has been experimentally verified. Alsubaie has also made significant advances in addressing a critical practical challenge in ILC: the selection of the initial input signal. His work shows that trial-to-trial error convergence depends heavily on this initial choice, and he has developed both model-based and experience-based techniques—using data from previous applications—to construct better starting inputs (12 and 6 citations). His research emphasizes robustness and load disturbance handling in state-based ILC schemes (7 citations), bridging theory with real-world industrial applications where periodic disturbances are common. Through experimental validation and dual-design methodologies, Alsubaie’s work provides engineers with practical tools for improving the performance of systems that operate repetitively, from manufacturing robotics to process control.
Research Focus
Key Achievements
Top Papers
- 1
- 2Initial Input Selection for Iterative Learning Control12 citations · 2011
- 3
- 4
- 5ILC Initial Input Selection with Experimental Verification2 citations · 2009
- 6