Abstract
This paper discusses designing of weights for both mixed-sensitivity and signal-based H∞ controller synthesis for active magnetic bearing (AMB) systems using genetic algorithm (GA) optimization. In mixed-sensitivity problem formulation, the weights represent desired upper bounds to closed loop transfer functions and in signal-based problem formulation, the weights represent desired system response under sinusoidal exogenous inputs. In order to cast weight design process as an optimization problem, appropriate cost functions are chosen to guarantee that desired performance objectives are satisfied with a stable controller. First, the validity of the method is demonstrated in simulation by comparing performances achieved using weights designed through the optimization to the weights selected as performance objectives. Then, the weight design via GA for H∞ controller synthesis is tested experimentally on a small AMB test rig in a disturbance rejection scheme. The designed H∞ controllers are implemented on the AMB system and tested up to the maximum design speed of 6000 rpm, where the rotor safely passed the first critical speed. Achieved performances are compared to a benchmark PID controller. Results demonstrate validity of using GA for weights design and show the superiority of H∞ controllers over PID controller for disturbance rejection in AMB systems.
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References
Sawicki, J.T., Maslen, E.H., Bischof, K.R.: Modeling and performance evaluation of machining spindle with active magnetic bearings. J. Mech. Sci. Technol. 21(6), 847–850 (2007)
Glover, K., McFarlane, D.: Robust Controller Design Using Normalized Coprime Factor Plant Descriptions. 138. Springer, Heidelberg (1990)
Kwakernaak, H.: Robustness optimization of linear feedback systems. In: The 22nd IEEE Conference on Decisions and Control, San Antonio, TX, USA, pp. 618–624 (1983)
Skogestad, S., Postlethwaite, I.: Multivariable Feedback Control: Analysis and Design, 2nd edn. Wiley, Chichester (2007)
Fujita, M., Hatake, K., Matsumura, F.: Loop shaping based robust control of a magnetic bearing. IEEE Control Syst. Mag. 13(4), 57–65 (1993)
Sivrioglu, S., Nonami, K.: LMI approach to gain scheduled H∞ control beyond PID control for gyroscopic rotor-magnetic bearing system. In: Proceeding of the 35th Conference on Decision and Control, Kobe, Japan, pp. 3694–3699 (1996)
Noshadi, A., Shi, J., Lee, S., Shi, P., Kalam, A.: System identification and robust control of multi-input multi-output active magnetic bearing systems. IEEE Trans. Control Syst. Technol. 24(4), 1227–1239 (2016)
Lundstörm, P., Skogestad, S., Wang, Z.Q.: Uncertainty weight selection for H-infinity and mu-control methods. In: Proceedings of the 30th IEEE Conference on Decision and Control, Brighton, UK, pp. 1537–1542 (1991)
Christiansson, A.K., Lennartson, B.: Weight selection for H∞ control using genetic algorithm. IFAC Proc. Vol. 32(2), 1043–1048 (1999)
Jastrzebski, R.P., Hynynen, K.M., Smirnov, A.: H∞ control of active magnetic suspension. Mechan. Syst. Sig. Process. 24(4), 995–1006 (2010)
Schweitzer, G., Maslen, E.H.: Magnetic Bearing: Theory, Design, and Application to Rotating Machinery. Springer, New York (2009)
ISO 14839-3: Mechanical vibration – Vibration of rotating machinery equipped with active magnetic bearings – Part 3: Evolution of stability margin. International Organization for Standardization ISO (2006)
Doyle, J.C.: Analysis of feedback systems with structured uncertainties. IEEE Proc. D - Control Theory Appl. 129(6), 242–250 (1982)
Sawicki, J.T., Maslen, E.H.: Toward automated AMB controller tuning: progress in identification and synthesis. In: Proceeding of 11th ISMB Conference, Nara, Japan, pp. 68–74 (2008)
Goldberg, D.E.: Genetic Algorithms in Search, Optimization & Machine Learning. Addison-Wesley, Boston (1989)
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Sahinkaya, A., Sawicki, J.T. (2019). Application of Genetic Algorithm for Synthesis of H∞ Controllers for Active Magnetic Bearing Systems. In: Cavalca, K., Weber, H. (eds) Proceedings of the 10th International Conference on Rotor Dynamics – IFToMM . IFToMM 2018. Mechanisms and Machine Science, vol 62. Springer, Cham. https://doi.org/10.1007/978-3-319-99270-9_1
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DOI: https://doi.org/10.1007/978-3-319-99270-9_1
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