Research Article
Design of Genetic Algorithm Based Robust LQG Controller for Active Magnetic Bearing System
@INPROCEEDINGS{10.1007/978-3-030-93709-6_15, author={Enderias Alemayehu Workeye and Tamiru Getahun G/Meskel and Yakob Kiros T/Himanot}, title={Design of Genetic Algorithm Based Robust LQG Controller for Active Magnetic Bearing System}, proceedings={Advances of Science and Technology. 9th EAI International Conference, ICAST 2021, Hybrid Event, Bahir Dar, Ethiopia, August 27--29, 2021, Proceedings, Part I}, proceedings_a={ICAST}, year={2022}, month={1}, keywords={Active magnetic bearing Genetic algorithm Linear quadratic Gaussian Kalman filter}, doi={10.1007/978-3-030-93709-6_15} }- Enderias Alemayehu Workeye
Tamiru Getahun G/Meskel
Yakob Kiros T/Himanot
Year: 2022
Design of Genetic Algorithm Based Robust LQG Controller for Active Magnetic Bearing System
ICAST
Springer
DOI: 10.1007/978-3-030-93709-6_15
Abstract
The Active Magnetic Bearing system (AMB) is a mechatronic device which is used to suspend rotating parts of a machine so that they rotate without contact to the stationary part of the machine. AMBs are highly nonlinear, non-minimum phase and inherently unstable. This paper has aimed to obtain a robust optimal state-feedback control system for the stabilization of the AMB System, with the help of Genetic algorithm (GA) as an optimization tool which will solve the tedious manual tuning of the weighting matrices in the design of linear quadratic regulator (LQR) and linear quadratic Gaussian (LQG).
The system’s mathematical model has been developed and also the properties of the uncontrolled system have been analyzed. Since AMB is a MIMO system, the interaction of the inputs with the outputs has been analyzed using relative gain array analysis and frequency domain analysis of the system transfer functions. Then, the optimal state feedback controllers have been developed. Here, LQR and LQG controllers are developed.
Finally, Comparative analysis between the controllers and between the design methods was carried out. The proposed GA based design methodology has resulted good Performance. In addition, the GA based design has also resulted improvements in robustness of the control systems. As far as gain margin (GM) and phase margin (PM) are concerned GA has resulted increase of 8.010–4db and 6.0210–3° in GM and PM respectively for LQR. Whereas, in LQG GA has resulted an increase of 3.810–5db and 2.5410–4°.
