Abstract
This proposal suggests a novel nonlinear position-stabilizing controller for magnetic levitation (MAGLEV) applications. The proposed scheme is devised by combining the active damping injection technique and disturbance observers (DOBs), considering the inherent nonlinear dynamics, as well as parameter and load variations. The convergence and performance recovery properties are obtained by analyzing the closed-loop dynamics, which is the main contribution. The numerical verification confirms a considerable closed-loop robustness improvement, compared with the cascade-type feedback-linearization controller.
Highlights
Magnetic levitation (MAGLEV) systems utilize an electromagnetic force to control the system body position
The MAGLEV system dynamics are strongly nonlinear, but they can be separated into slow mechanical dynamics and fast electrical dynamics [10,11]
The widening feasible operating region issue was handled by the additional gain-scheduling algorithm [13], particle swarm optimization [14], the state-feedback technique with convex optimization [15], and the adaptation algorithm for updating feedback gains [5]
Summary
Magnetic levitation (MAGLEV) systems utilize an electromagnetic force to control the system body position. The MAGLEV system dynamics are strongly nonlinear, but they can be separated into slow mechanical dynamics and fast electrical dynamics [10,11] Using this concept and linearization technique, a simple proportional-integral (PI) regulator was used to stabilize the current-loop (inner) and velocity/position-loop (outer) with a well-tuned feedback gain obtained by the time and frequency domain analysis [12]. The widening feasible operating region issue was handled by the additional gain-scheduling algorithm [13], particle swarm optimization [14], the state-feedback technique with convex optimization [15], and the adaptation algorithm for updating feedback gains [5] These techniques still required the use of a linearized model of MAGLEV systems. The realistic numerical simulation results verify the effectiveness of the proposed algorithm by showing the closed-loop robustness improvement with MATLAB/Simulink
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
