A derivative-free kalman filtering approach to state estimation-based control of nonlinear systems

IEEE Transactions on Industrial Electronics

Volumn 59, Issue 10, 2012, Pages 3987-3997

  Rigatos, Gerasimos G ^a  

^a INDUSTRIAL SYSTEMS INSTITUTE   (Greece)

Author keywords

Filtering algorithms; Kalman filters; nonlinear control systems; sensorless control; state estimation

Indexed keywords

BEARINGS (MACHINE PARTS); DC MOTORS; EXTENDED KALMAN FILTERS; GAUSSIAN NOISE (ELECTRONIC); KALMAN FILTERS; LINEARIZATION; NONLINEAR CONTROL SYSTEMS; NONLINEAR SYSTEMS; RISK PERCEPTION; SENSORLESS CONTROL; STATE ESTIMATION;

EFFICIENT IMPLEMENTATION; FILTERING ALGORITHM; LINEARIZATION APPROXIMATION; NONLINEAR KALMAN FILTERING; NONLINEAR STATE ESTIMATION; STANDARD KALMAN FILTERS; STATE ESTIMATION-BASED CONTROLS; UNSCENTED KALMAN FILTER;

NONLINEAR ANALYSIS;

EID: 84860482955     PISSN: 02780046     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIE.2011.2159954     Document Type: Article

References (47)

1. E. W. Kamen and J. K. Su, Introduction to Optimal Estimation. New York: Springer-Verlag, 1999.
2. M. Bassevile and I. Nikoforov, Detection of Abrupt Changes: Theory and Applications. Englewood Cliffs, NJ: Prentice-Hall, 1993.
3. C. Harris, X. Hong, and Q. Gan, Adaptive Modelling, Estimation and Fusion From Data. New York: Springer-Verlag, 2002.
4. G. W. Ng, Intelligent Systems-Fusion, Tracking and Control. Hertfordshire, U.K.: Research Studies Press, 2003.
5. J. Xiong, An Introduction to Stochastic Filtering Theory. London, U.K.: Oxford Univ. Press, 2008.
6. G. G. Rigatos and S. G. Tzafestas, Extended Kalman Filtering for Fuzzy Modelling and Multi-Sensor Fusion, Mathematical and Computer Modelling of Dynamical Systems. New York: Taylor & Francis, 2007, pp. 251-266.
7. G. Rigatos and Q. Zhang, "Fuzzy model validation using the local statistical approach," Publication Interne IRISA No 1417, Rennes, France, 2001.
8. G. G. Rigatos, "Particle filtering for state estimation in industrial robotic systems," IMeche J. Syst. Control Eng., vol. 222, no. 6, pp. 437-455, 2008.
9. G. G. Rigatos, "Particle filtering for state estimation in nonlinear industrial systems," IEEE Trans. Instrum. Meas., vol. 58, no. 11, pp. 3885-3900, Nov. 2009.
10. S. Julier, J. Uhlmann, and H. F. Durrant-Whyte, "A new method for the nonlinear transformations of means and covariances in filters and estimators," IEEE Trans. Autom. Control, vol. 45, no. 3, pp. 477-482, Mar. 2000.
11. S. J. Julier and J. K. Uhlmann, "Unscented filtering and nonlinear estimation," Proc. IEEE, vol. 92, no. 3, pp. 401-422, Mar. 2004.
12. R. van der Merwe, E. A.Wan, and S. I. Julier, "Sigma-point Kalman filters for nonlinear estimation and sensor-fusion: Applications to intergrated navigation," in Proc. AIAA Guid., Navig. Control Conf., Providence, RI, 2004, pp. 1-30.
13. S. Särrka, "On unscented Kalman filtering for state estimation of continuous-time nonlinear systems," IEEE Trans. Autom. Control, vol. 52, no. 9, pp. 1631-1641, Sep. 2007.
14. R. Kandepu, B. Foss, and L. Imsland, "Applying the unscented Kalman filter for nonlinear state estimation," J. Process Control, vol. 18, no. 7/8, pp. 753-768, Aug./Sep. 2008.
15. G. G. Rigatos, "A derivative-free Kalman filtering approach for sensorless control of nonlinear systems," in Proc. IEEE ISIE, Bari, Italy, Jul. 2010, pp. 2049-2054.
16. Y. Chinniah, R. Burton, and S. Habibi, "Failure monitoring in a high performance hydrostatic actuation system using the extended Kalman filter," Mechatronics, vol. 16, pp. 643-653, 2006.
17. A. Seguritan and M. Rotuno, "Torque pulsation compensation for a DC motor using an extended Kalman filter approach," in Proc. 41sl IEEE Conf. Decision Control, Las Vegas, NV, Dec. 2002, pp. 486-491.
18. J. M. Lin, M. C. Lin, and H. P. Wang, "LEQG/LTR controller design with extended Kalman filter for sensorless brushless DC driver," Comput. Methods Appl. Mech. Eng., vol. 190, no. 42, pp. 5481-5494, Aug. 2001.
19. Y. Liu, Z. Q. Zhu, and D. Howe, "Instantaneous torque estimation in sensorless direct-torque-controlled brushless DC motors," IEEE Trans. Ind. Appl., vol. 42, no. 5, pp. 1275-1283, Sep./Oct. 2006.
20. B. Terzic and M. Jadric, "Design and implementation of the extended Kalman filter for the speed and rotor position estimation of brushless DC motor," IEEE Trans. Ind. Electron., vol. 48, no. 6, pp. 1065-1073, Dec. 2001.
21. D. Efimov, A. Zolghadri, and P. Simon, "Improving fault detection abilities of extended Kalman filters by covariance matrices adjustment," in Proc. Conf. Control Fault Tolerant Syst., Nice, France, Oct. 6-8, 2010, pp. 131-136.
22. S. K. Yang, "An experiment of state estimation for predictive maintenance using Kalman filter on a DC motor," Reliab. Eng. Syst. Saf., vol. 75, no. 1, pp. 103-111, Jan. 2002.
23. L. An and L. Sepehri, "Leakage fault identification in a hydraulic positioning system using extended Kalman filter," in Proc. Amer. Control Conf., Boston, MA, Jun./Jul. 2004, pp. 3088-3093.
24. R. Marino, "Adaptive observers for single output nonlinear systems," IEEE Trans. Autom. Control, vol. 35, no. 9, pp. 1054-1058, Sep. 1990.
25. R. Marino and P. Tomei, "Global asymptotic observers for nonlinear systems via filtered transformations," IEEE Trans. Autom. Control, vol. 37, no. 8, pp. 1239-1245, Aug. 1992.
26. W. Lin and H. Wang, "Linearization techniques in fault diagnosis of non-linear systems," in Proc. Inst. Mech. Eng. Part I, 2000, vol. 214, pp. 241-245.
27. D. Boutat, A. Benali, H. Hammouri, and K. Busawond, "New algorithm for observer error linearization with a diffeomorphism on the outputs," Automatica, vol. 45, no. 10, pp. 2187-2193, Oct. 2009.
28. D. Noh, N. H. Jo, and J. H. Seo, "Nonlinear observer design by dynamic observer error linearization," IEEE Trans. Autom. Control, vol. 49, no. 10, pp. 1746-1753, Oct. 2004.
29. J. Back, K. T. Yu, and J. H. Seo, "Dynamic observer error linearization," Automatica, vol. 42, no. 12, pp. 2195-2200, Dec. 2006.
30. J. Chiasson, "Nonlinear differential-geometric techniques for control of a series DC motor," IEEE Trans. Control Syst. Technol., vol. 2, no. 1, pp. 35-42, Mar. 1994.
31. J. Holtz, "Sensorless control of induction motor drives," Proc. IEEE, vol. 90, no. 8, pp. 1359-1394, Aug. 2002.
32. B. Akin, U. Orguner, A. Ersak, and M. Ehsani, "Simple derivative-free nonlinear state observer for sensorless AC drives," IEEE/ASME Trans. Mech., vol. 11, no. 5, pp. 634-643, Oct. 2006.
33. M. Hilairet, F. Augerb, and E. Berthelot, "Speed and rotor flux estimation of induction machines using a two-stage extended Kalman filter," Automatica, vol. 45, no. 8, pp. 1819-1827, Aug. 2009.
34. P. Borsje, T. F. Chan, Y. K. Wong, and S. L. Ho, "A comparative study of Kalman filtering for sensorless control of a permanent-magnet synchronous motor drive," in Proc. IEEE Int. Conf. Elect. Mach. Drives, San Antonio, TX, 2005, pp. 815-822.
35. H. S. Wang and Y. T. Liu, "Integrated design of speed-sensorless and adaptive speed controller for a brushless DC motor," IEEE Trans. Power Electron., vol. 21, no. 2, pp. 518-523, Mar. 2006.
36. J. S. H. Tsai, M. H. Lin, C. H. Zheng, S. M. Guo, and L. S. Shieh, "Actuator fault detection and performance recovery with Kalman filterbased adaptive observer," Int. J. Gen. Syst., vol. 36, no. 4, pp. 375-398, 2007.
37. O. Moseler and R. Isermann, "Application of model-based fault detection to a brushless DC motor," IEEE Trans. Ind. Electron., vol. 47, no. 5, pp. 1015-1020, Oct. 2000.
38. N. Salvatore, A. Caponio, F. Neri, S. Stasi, and G. L. Cascella, "Optimization of delayed-state Kalman-filter-based algorithm via differential evolution for sensorless control of induction motors," IEEE Trans. Ind. Electron., vol. 57, no. 1, pp. 385-394, Jan. 2010.
39. C. Mitsantisuk, S. Katsura, and K. Ohishi, "Kalman-filter-based sensor integration of variable power assist control based on human stiffness estimation," IEEE Trans. Ind. Electron., vol. 56, no. 10, pp. 3897-3905, Oct. 2009.
40. G. G. Rigatos, "Particle and Kalman filtering for fault diagnosis in DC motors," in Proc. 5th IEEE VPPC, Dearborn, MI, Sep. 2009, pp. 1228-1235.
41. G. G. Rigatos, "Particle and Kalman filtering for state estimation and control of DC motors," ISA Trans., vol. 48, no. 1, pp. 62-72, Jan. 2009.
42. J. H. Horng, "Neural adaptive tracking control of a DC motor," Inf. Sci., vol. 118, no. 1-4, pp. 1-13, Sep. 1999.
43. G. G. Rigatos, "Adaptive fuzzy control of DC motors using state and output feedback," Elect. Power Syst. Res., vol. 79, no. 11, pp. 1579-1592, Nov. 2009.
44. K. Xiong, H. Y. Zhang, and C. W. Chan, "Performance evaluation of UKF-based nonlinear filtering," Automatica, vol. 42, no. 2, pp. 261-270, Feb. 2006.
45. R. Cortesao, J. Park, and O. Khatib, "Real-time adaptive control for haptic tele-manipulation with Kalman active observers," IEEE Trans. Robot., vol. 22, no. 5, pp. 987-999, Oct. 2006.
46. Y. Xia, Z. Zhu, M. Fu, and S. Wang, "Attitude tracking of rigid spacecraft with bounded disturbances," IEEE Trans. Ind. Electron., vol. 58, no. 2, pp. 647-659, Feb. 2011.
47. G. G. Rigatos, Modelling and Control for Intelligent Industrial Systems: Adaptive Algorithms in Robotics and Industrial Engineering. NewYork: Springer-Verlag, 2011.