http://iet.metastore.ingenta.com
1887

Adaptive general predictive controller for nonlinear systems

Adaptive general predictive controller for nonlinear systems

For access to this article, please select a purchase option:

Buy article PDF
$19.95
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
Other:
 
IEE Proceedings D (Control Theory and Applications) — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

A nonlinear general predictive controller (NLGPC) is described which is based on the use of a Hammerstein model within a recursive control algorithm. A key contribution of the paper is the use of a novel, one-step simple root solving procedure for the Hammerstein model, this being a fundamental part of the overall tuning algorithm. A comparison is made between NLGPC and nonlinear deadbeat control (NLDBC) using the same one-step nonlinear components, in order to investigate NLGPC advantages and disadvantages.

References

    1. 1)
      • C. Harris , S. Billings . (1985) , Self-tuning control: theory and applications.
    2. 2)
      • K. Warwick . (1988) , Implementation of self-tuning controllers.
    3. 3)
      • D.P. Atherton . , Nonlinear control engineering.
    4. 4)
      • P.A. Cook . (1986) , Nonlinear dynamical systems.
    5. 5)
      • K. Anbumani , L.M. Patnoik , I.G. Sarma . Self-tuning minimum variance control of nonlinear systems of the Hammerstein model. IEEE Trans. , 4 , 959 - 961
    6. 6)
      • Lachmann, K.H.: `Parameter adaptive control of a class of non linear processes', Proc. 6th IFAC Symposium on Identification and System Parameter Estimation, 1982, , p. 372–378.
    7. 7)
      • M. Agarwal , D.E. Seborg . Self-tuning controllers for nonlinear systems. Automatica , 2 , 204 - 214
    8. 8)
      • D.W. Clarke , C. Mohtadi , P.S. Tuffs . General pre dictive control. Automatica , 3 , 137 - 160
    9. 9)
      • S.A. Billings , S.Y. Fakhouri . Theory of separable processes with applications to the identification of nonlinear systems. Proc. IEEE , 9 , 1051 - 1058
    10. 10)
      • M.J. Grimble . Observations-weighted minimum-variance control of linear and nonlinear systems. Int. J. Syst. Sci. , 12 , 1481 - 1492
    11. 11)
      • Keviczky, L., Vajk, I., Hetfhessy, J.: `A self-tuning extremal controller for the generalised Hammerstein model', Proc. 5th IFAC Symposium on Identification and System Parameter Estimation, 1979, p. 1147–1151, Darmstadt.
    12. 12)
      • Al-Assaf, Y.: `Self-tuning control theory and application', 1988, DPhil Thesis, Oxford University.
    13. 13)
      • A.N. Payne . One-step-ahead control subject to an input-amplitude constraint. Int. J. Control , 1257 - 1269
    14. 14)
      • T.C. Tsang , D.W. Clarke . Generalised predictive control with input constraints. Proc. IEE, Control Theory & Appl. , 6 , 451 - 460
    15. 15)
      • K. Warwick . Adaptive deadbeat control of stochastic systems. Int. J. Control , 3 , 651 - 664
    16. 16)
      • Voss, G.: `Simulation of a chemical reaction process', 1980, Diploma thesis TH, Darmstadt.
    17. 17)
      • P.S. Tuffs , D.W. Clarke . Self-tuning control of offset; a unified approach. Proc. IEE, Control Theory & Appl. , 3 , 100 - 110
    18. 18)
      • Kortmann, M., Unbehauen, H.: `Identification methods for nonlinear MISO systems', Proc. IFAC World Congress, 1987, Munich, p. 225–230.
    19. 19)
      • Owens, D.H., Warwick, K.: `Extended predictive control', Proc. IEE International Conference, 1988, , p. 622–627, Control 88.
    20. 20)
      • K. Warwick , D.W. Clarke . Weighted input predictive controller. Proc. IEE, Control Theory & Appl. , 1 , 16 - 20
    21. 21)
      • Keviczky, L., Haber, R.: `Adaptive dual extremum control by Hammerstein models', Proc. IFAC Symposium on Stochastic Control, 1974, Budapest, p. 333–341.
    22. 22)
      • C.F. Gerald . (1978) , Applied numerical analysis.
    23. 23)
      • H. Kurz , R. Isermann , R. Schumann . Experimental comparison and application of various parameter adaptive control algorithms. Automatica , 117 - 133
    24. 24)
      • Ljung, L., Wittenmark, B.: Report 7404, 1974.
    25. 25)
      • M. Farsi , K.J. Zachariah , K. Warwick , K. Warwick , A. Pugh . (1988) Adaptive control algorithms for intelligent robot manipulators, Robot control: theory and applicatons.
    26. 26)
      • Warwick, K., Zhu, Q.M., Douce, J.L.: `An adaptive con troller for nonlinear systems', Proc. 3rd IFAC Symposium on Adaptive Control and Signal Processing, 1989, Glasgow, p. 651–656.

Related content

content/journals/10.1049/ip-d.1991.0005
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address