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Enhancing working performance of active magnetic bearings using improved fuzzy control and Kalman-LMS filter. (English) Zbl 1361.93047
Summary: This paper develops a novel control approach to enhance working performance of eight-pole radial active magnetic bearings (AMB). In the proposed method, the improved fuzzy proportional-integral-derivative (PID) control based on variable universes of proportional scaling is designed firstly to obtain better identification performance and flexibility of AMB control. Then, a Kalman filter is implemented to estimate the rotor displacement to reduce the noise disturbance and undesirable parameter adjustments caused by fuzzy control scheme. Finally, the least mean square (LMS) filter is connected with fuzzy control to compensate the unknown mass unbalance which might induce serious vibrations of AMB facilities. Thesimulation results show that the improved fuzzy PID control plays better performance than PID control in overshoot control, and the transient time of improved fuzzy PID is much shorter compared to conventional fuzzy PID. Meanwhile, the impacts of noise disturbance can be significantly limited by connecting with Kalman filter, and the maximum steady-state error can be decreased to about 85%. It is also shown that the LMS filter algorithm can effectively compensate the unknown mass unbalance in relatively short time without affecting the stability of AMB system.
MSC:
93C95 Application models in control theory
93C42 Fuzzy control/observation systems
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[1] Barthod, Degrees of freedom control of a magnetically levitated rotor, IEEE Transactions on Magnetics 31 pp 4202– (1995) · doi:10.1109/20.489926
[2] Polajzer, Decentralized PI/PD position control for active magnetic bearings, Electrical Engineering 89 pp 53– (2006) · doi:10.1007/s00202-005-0315-1
[3] Su, Study on active magnetic bearing based on Matlab, Journal of Wuhan Institute of Chemical Technology 25 pp 51– (2003)
[4] Chen, Optimal fuzzy PID controller design of an active magnetic bearing system based on adaptive genetic algorithms, Proceedings of the Seventh International Conference on Machine Learning and Cybernetics pp 2054– (2008)
[5] Chen, Robust nonsingular terminal sliding-mode control for nonlinear magnetic bearing system, IEEE Transactions on Control Systems Technology 19 pp 636– (2011) · doi:10.1109/TCST.2010.2050484
[6] Al-Muthairi, Sliding mode control of a magnetic levitation system, Mathematical Problems in Engineering 2 pp 93– (2004) · Zbl 1130.93324 · doi:10.1155/S1024123X04310033
[7] Xu, Design and complementation of magnetic bearing on H  theory, China Mechanical Engineering 17 pp 1060– (2006)
[8] Chen, Robust control of a voltage-controlled three-pole active magnetic bearing system, IEEE/ASME Transactions on Mechatronics 15 pp 381– (2010) · doi:10.1109/TMECH.2009.2027015
[9] Agarwal, Fuzzy logic control of three-pole active magnetic bearing system, International Journal of Modelling, Identification and Control 12 pp 395– (2011) · doi:10.1504/IJMIC.2011.040083
[10] Trent, Full state feedback control of a magnetic bearing system using optimal estimation, 20th IEEE International conference on Industrial Electronics, Control and Instrumentation pp 2069– (1994)
[11] Matsuda, Self-sensing three-pole magnetic bearing using a kalman filter, SICE-ICASE International Joint Conference pp 1590– (2006)
[12] Schuhmann, Improving operational performance of active magnetic bearings using Kalman filter and state feedback control, IEEE Transactions on Industrial Electronics 59 pp 821– (2012) · doi:10.1109/TIE.2011.2161056
[13] Mou, Research unbalance compensation of active magnetic bearing, Bearing 11 pp 10– (2002)
[14] Bleuler, Application of digital signal processors for industrial magnetic bearings, IEEE Transactions on Control Systems Technology 2 pp 280– (1994)
[15] Yoo, Optimal Notch filter for active magnetic bearing controllers, 2011 IEEE/ASME International Conference on Advanced Intelligent Mechatronics pp 707– (2011) · doi:10.1109/AIM.2011.6027087
[16] Lee, Unbalance compensation on AMB system without a rotational sensor, Mechanical Systems Machine Elements & Manufacturing 46 pp 423– (2003)
[17] Fan, Knowledge-based fuzzy imbalanced force compensator design for a single active magnetic bearing suspended rotor system, 2011 IEEE International Conference on Fuzzy Systems pp 867– (2011) · doi:10.1109/FUZZY.2011.6007545
[18] Jiang, Adaptive unbalance compensation control of a magnetic bearing supporting rotor system, Journal of Zhejiang University (Engineering Science) 45 pp 503– (2011)
[19] Schweitzer, Magnetic Bearings: Theory, Design, and Application to Rotating Machinery (2012)
[20] Hu, The basic theory and application of magnetic bearing (2006)
[21] Bleuler, Application of digital signal processors for industrial magnetic bearings, IEEE Transactions on Control Systems Technology 2 pp 280– (1994) · doi:10.1109/87.338647
[22] Welch, An introduction to the Kalman filter, Proc of Siggraph 8 pp 27599– (2001)
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