Hunting Based Optimization Techniques used in Controlling an Active Magnetic Bearing System

This paper proposes a closed-loop and implements some metaheuristic optimization approaches to regulate an unstable active magnetic bearing (AMB) system. First of all, hardware model AMB is fabricated in the laboratory. Mathematical analysis carried out linearized open-loop transfer function obtained for equilibrium point operation, using parameters model. Then, closed loop proposed this system, which comprises PID controller, power amplifier, position sensor. Further, three different nature-inspired hunting-based algorithms i.e., Ant lion (ALO), Grey wolf (GWO), Whale algorithm (WOA) are implemented individually calculate gain controller. Separately, performance these evaluated observed on four indices: integral absolute error (IAE), squared (ISE), time multiplied (ITAE) (ITSE). For stable, efficient, reliable it vital perform techniques with objective functions Therefore, few comparisons conducted, first based data from statistical analysis. The second transient state phase margin. Third scale execution time. Finally, assistance effectiveness each technique control system concluded can serve as theoretical experimental foundations continued use high-speed applications.