Optimized magnetic field control of an electromagnetic actuation system for enhanced microrobot manipulation. (August 2022)

• Record Type: Journal Article
• Authors: Hoang, Manh Cuong; Kim, Jayoung; Park, Jong-Oh; Kim, Chang-Sei
• Is Part Of: Mechatronics. Volume 85(2022)
• Publication Date: 2022-08
• Subjects: Magnetic actuation system -- Medical microrobot -- Magnetic field optimization -- Pareto frontier; Computer integrated manufacturing systems -- Periodicals; Flexible manufacturing systems -- Periodicals; Mechatronics -- Periodicals; Productique -- Périodiques; Fabrication, Systèmes flexibles de -- Périodiques; Mécatronique -- Périodiques; Computer integrated manufacturing systems; Flexible manufacturing systems; Mechatronics; Periodicals; 629.89
• DOI: 10.1016/j.mechatronics.2022.102830
• Languages: English
• ISSNs: 0957-4158

Abstract

Highlights: Magnetic field optimization method of an electromagnetic navigation for a microrobot. Single- and multiple-object optimization to solve magnetic field inverse problem. Simulation and experimental validation of improved strength and gradient. Closed-loop control for a magnetic particle to verify the navigation performance. Practical applicability through comparison with conventional benchmark system. Abstract: This paper presents a novel magnetic field control method to enhance the performance in terms of accuracy and field strength of underdetermined electromagnetic actuation systems. Conventional control algorithms prioritize low overall power usage, and they fail to cope with the saturation of electromagnets due to a limited power supply, which limits the magnetic and gradient field strength of a system. In this study, we prioritize magnetic and gradient fields, among other priorities, by developing computational optimization programming to find alternative solutions that satisfy constraints. Single- and multi-objective optimization techniques are developed and compared to address the problem. The latter algorithm, which employs the weighted sum method to obtain Pareto-optimal solutions, demonstrates better performance than the former one. The proposed control methodology is characterized and validated by simulation and experiments. The maximum magnetic and gradient fields were significantly enhanced by the proposed algorithm; by approximately 35% and 70%, respectively, compared to the conventional independent control applied for our system and by 24% and 64%, respectively, for a benchmark system.