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State estimation for a class of nonlinear systems

Benoît Schwaller; Denis Ensminger; Birgitta Dresp-Langley; José Ragot

International Journal of Applied Mathematics and Computer Science (2013)

  • Volume: 23, Issue: 2, page 383-394
  • ISSN: 1641-876X

Abstract

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We propose a new type of Proportional Integral (PI) state observer for a class of nonlinear systems in continuous time which ensures an asymptotic stable convergence of the state estimates. Approximations of nonlinearity are not necessary to obtain such results, but the functions must be, at least locally, of the Lipschitz type. The obtained state variables are exact and robust against noise. Naslin's damping criterion permits synthesizing gains in an algebraically simple and efficient way. Both the speed and damping of the observer response are controlled in this way. Model simulations based on a Sprott strange attractor are discussed as an example.

How to cite

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Benoît Schwaller, et al. "State estimation for a class of nonlinear systems." International Journal of Applied Mathematics and Computer Science 23.2 (2013): 383-394. <http://eudml.org/doc/257116>.

@article{BenoîtSchwaller2013,
abstract = {We propose a new type of Proportional Integral (PI) state observer for a class of nonlinear systems in continuous time which ensures an asymptotic stable convergence of the state estimates. Approximations of nonlinearity are not necessary to obtain such results, but the functions must be, at least locally, of the Lipschitz type. The obtained state variables are exact and robust against noise. Naslin's damping criterion permits synthesizing gains in an algebraically simple and efficient way. Both the speed and damping of the observer response are controlled in this way. Model simulations based on a Sprott strange attractor are discussed as an example.},
author = {Benoît Schwaller, Denis Ensminger, Birgitta Dresp-Langley, José Ragot},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {nonlinear systems; state observers; continuous time},
language = {eng},
number = {2},
pages = {383-394},
title = {State estimation for a class of nonlinear systems},
url = {http://eudml.org/doc/257116},
volume = {23},
year = {2013},
}

TY - JOUR
AU - Benoît Schwaller
AU - Denis Ensminger
AU - Birgitta Dresp-Langley
AU - José Ragot
TI - State estimation for a class of nonlinear systems
JO - International Journal of Applied Mathematics and Computer Science
PY - 2013
VL - 23
IS - 2
SP - 383
EP - 394
AB - We propose a new type of Proportional Integral (PI) state observer for a class of nonlinear systems in continuous time which ensures an asymptotic stable convergence of the state estimates. Approximations of nonlinearity are not necessary to obtain such results, but the functions must be, at least locally, of the Lipschitz type. The obtained state variables are exact and robust against noise. Naslin's damping criterion permits synthesizing gains in an algebraically simple and efficient way. Both the speed and damping of the observer response are controlled in this way. Model simulations based on a Sprott strange attractor are discussed as an example.
LA - eng
KW - nonlinear systems; state observers; continuous time
UR - http://eudml.org/doc/257116
ER -

References

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  1. Abdessameud, A. and Khelfi, M.F. (2006). A variable structure observer for the control of robot manipulators, International Journal of Applied Mathematics and Computer Science 16(2): 189-196. Zbl1111.93056
  2. Bastin, G. and Gevers, M. (1988). Stable adaptive observers for nonlinear time-varying systems, IEEE Transactions on Automatic Control 33(7): 650-658. Zbl0676.93037
  3. Besançon, G., Voda, A. and Jouffroy, G. (2010). A note on state and parameter estimation in a Van der Pol oscillator, Automatica 46(10): 1735-1738. Zbl1203.93032
  4. Besançon, G., Zhang, Q. and Hammouri, H. (2004). High gain observer based state and parameter estimation in nonlinear systems, 6th IFAC Symposium on Nonlinear Control Systems, NOLCOS, Stuttgart, Germany, pp. 325-332. 
  5. Bestle, D. and Zeitz, M. (1983). Canonical form observer design for non-linear time-variable systems, International Journal of Control 38(2): 419-431. Zbl0521.93012
  6. Bodizs, L., Srinivasan, B. and Bonvin, D. (2011). On the design of integral observers for unbiased output estimation in the presence of uncertainty, Journal of Process Control 21(3): 379-390. 
  7. Boizot, N., Busvelle, E. and Gauthier, J. (2010). An adaptive high-gain observer for nonlinear systems, Automatica 46(9): 1483-1488. Zbl1201.93122
  8. Boutat, D., Benali, A., Hammouri, H. and Busawon, K. (2009). New algorithm for observer error linearization with a diffeomorphism on the outputs, Automatica 45(10): 2187-2193. Zbl1179.93050
  9. Boutayeb, M. and Aubry, D. (1999). A strong tracking extended Kalman observer for nonlinear discrete-time systems, IEEE Transactions on Automatic Control 44(8): 1550-1556. Zbl0957.93086
  10. Chen, W., Khan, A.Q., Abid, M. and Ding, S.X. (2011). Integrated design of observer based fault detection for a class of uncertain nonlinear systems, International Journal of Applied Mathematics and Computer Science 21(3): 423-430, DOI: 10.2478/v10006-011-0031-0. Zbl1234.93036
  11. Ciccarella, G., Mora, M. D. and Germani, A. (1993). A Luenberger-like observer for nonlinear systems, International Journal of Control 57(3): 537-556. Zbl0772.93018
  12. Efimov, D. and Fridman, L. (2011). Global sliding-mode observer with adjusted gains for locally Lipschitz systems, Automatica 47(3): 565-570. Zbl1216.93019
  13. Farza, M., M'Saad, M., Triki, M. and Maatoug, T. (2011). High gain observer for a class of non-triangular systems, Systems and Control Letters 60(1): 27-35. Zbl1207.93014
  14. Feki, M. (2009). Observer-based synchronization of chaotic systems, Chaos, Solitons and Fractals 39(3): 981-990. 
  15. Fliess, M. (1990). Generalized controller canonical forms for linear and nonlinear dynamics, IEEE Transactions on Automatic Control 35(9): 994-1001. Zbl0724.93010
  16. Fuller, A. (1992). Guest editorial, International Journal of Control 55(3): 521-527. 
  17. Gauthier, J. and Bornard, G. (1981). Observability for any u(t) of a class of nonlinear systems, IEEE Transactions on Automatic Control AC-26(4): 922-926. Zbl0553.93014
  18. Gauthier, J., Hammouri, H. and Othman, S. (1992). A simple observer for nonlinear systems: Applications to bioreactors, IEEE Transactions on Automatic Control 37(6): 875-880. Zbl0775.93020
  19. Ghosh, D., Saha, P. and Chowdhury, A. (2010). Linear observer based projective synchronization in delay Roessler system, Communications in Nonlinear Science and Numerical Simulation 15(6): 1640-1647. Zbl1221.34138
  20. Gille, J., Decaulne, P. and Pélegrin, M. (1988). Systèmes asservis non linéaires, 5 ième edn, Dunod, Paris, pp. 110-146. Zbl0189.45701
  21. Gißler, J. and Schmid, M. (1990). Vom Prozeß zur Regelung. Analyse, Entwurf, Realisierung in der Praxis, 1st Edn., Siemens, Berlin/Munich, pp. 350-399. 
  22. Hermann, R. and Krener, A. (1977). Nonlinear controllability and observability, IEEE Transactions on Automatic Control AC-22(5): 728-740. Zbl0396.93015
  23. Hui, S. and Żak, S.H. (2005). Observer design for systems with unknown inputs, International Journal of Applied Mathematics and Computer Science 15(4): 431-446. Zbl1127.93018
  24. Humbert, C. and Ragot, J. (1970). Comportement asymptotique des rapports caractéristiques dans l'optimisation quadratique, Revue A 12(1): 32-34. 
  25. Ibrir, S. (2009). Adaptive observers for time-delay nonlinear systems in triangular form, Automatica 45(10): 2392-2399. Zbl1179.93047
  26. Kim, Y.C., Keel, L.H. and Manabe. S.M. (2002). Controller design for time domain specifications, Proceedings of the 15th Triennial World Congress, Barcelona, Spain, pp. 1230-1235. 
  27. Khémiri, K., Ben Hmida, F., Ragot, J. and Gossa, M. (2011). Novel optimal recursive filter for state and fault estimation of linear stochastic systems with unknown disturbances, International Journal of Applied Mathematics and Computer Science 21(4): 629-637, DOI: 10.2478/v10006-011-0049-3. Zbl1283.93282
  28. Krener, A. and Isidori, A. (1983). Linearization by output injection and nonlinear observers, Systems & Control Letters 3(1): 47-52. Zbl0524.93030
  29. Luenberger, D. (1966). Observers for multivariable systems, IEEE Transactions on Automatic Control AC-11(2): 190-197. 
  30. Lyapunov, A. (1892). The General Problem of Motion Stability, Annals of Mathematics Studies, Vol. 17, Princeton University Press, (translated into English in 1949). Zbl0041.32204
  31. Morales, A. and Ramirez, J. (2002). A PI observer for a class of nonlinear oscillators, Physics Letters A 297(3-4): 205-209. Zbl0995.65057
  32. Naslin, P. (1960). Nouveau critère d'amortissement, Automatisme 5(6): 229-236. Zbl0095.31804
  33. Naslin, P. (1963). Polynomes normaux et critère algébrique d'amortissement, Automatisme 8(6): 215-223. 
  34. Raghavan, S. and Hedrick, J. (1994). Observer design for a class of nonlinear systems, International Journal of Control 59(2): 515-528. Zbl0802.93007
  35. Röbenack, K. and Lynch, A.F. (2004). An efficient method for observer design with approximately linear error dynamics, International Journal of Control 77(7): 607-612. Zbl1062.93008
  36. Röbenack, K. and Lynch, A. (2006). Observer design using a partial nonlinear observer canonical form, International Journal of Applied Mathematics and Computer Science 16(3): 333-343. Zbl1136.93313
  37. Shuang, C., Guodong, L. and Xianyong, F. (WCE 2010). Parameters identification of nonlinear DC motor model using compound evolution algorithms, Proceedings of the World Congress on Engineering, London, UK, pp. 15-20. 
  38. Sprott, J. (1994). Some simple chaotic flows, Physical Review E 50(2): 647-650. 
  39. Söffker, D., Yu, T. and Müller, P. (1995). State estimation of dynamical systems with nonlinearities by using proportional-integral observers, International Journal of Systems Science 26(9): 1571-1582. Zbl0830.93009
  40. Tornambè, A. (1992). High-gain observers for non-linear systems, International Journal of Systems Science 23(9): 1475-1489. Zbl0768.93013
  41. Veluvolu, K., Soh, Y. and Cao, W. (2007). Robust observer with sliding mode estimation for nonlinear uncertain systems, IET Control Theory and Applications 1(5): 1533-1540. Zbl1134.93032
  42. Zeitz, M. (1987). The extended Luenberger observer for nonlinear systems, Systems and Control Letters Archive 9(2): 149-156. Zbl0624.93012
  43. Zheng, G., Boutat, D. and Barbot, J. (2009). Multi-output dependent observability normal form, Nonlinear Analysis: Theory, Methods and Applications 70(1): 404-418. Zbl1152.93015

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