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Nonlinear model predictive control method for control nonaffine systems

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In the paper, it is proposed to modify the known nonlinear predictive control method with a dynamic linearization around the prediction error or current process variable measurements. The approach is intended for strongly nonlinear control nonaffine processes, particularly for those that can be modeled by generalized MIMO Hammerstein models. Such models are often used, for example, for modeling various processes in chemistry. The proposed nonlinear control method allows for control constraints through including appropriate approximating functions into the model input matrix. To minimize the plant-model mismatch, an auxiliary control loop is proposed, which creates an additional control signal from the difference between the model and the plant states.
Czasopismo
Rocznik
Strony
13--20
Opis fizyczny
Bibliogr. 18 poz., wykr.
Twórcy
autor
  • Institute of Control Engineering, Technical University of Szczecin, ul. Sikorskiego 37, 70-313 Szczecin, Poland
  • Institute of Control Engineering, Technical University of Szczecin, ul. Sikorskiego 37, 70-313 Szczecin, Poland
Bibliografia
  • [1] Allgower F., Zheng A., An overview of nonlinear model predictive control applications, Birk- hauser, 2000.
  • [2] Blet N.. Megias D., Serrano J., De Prada C., Nonlinear MPC versus MPC using on-line lineari-sation - comparative study, Proceedings of the 15th Triennial World Congress, Barcelona 2002.
  • [3] Camacho E. F., BordonsC., Model predictive control, Springer Verlag, 1999.
  • [4] Domek S., Indirect adaptive CRHPC algorithm for systems of the Hammerstein form, Proceedings of the 17th 1ASTED Int. Conf. on Modeling, Identification and Control, Grindelwald 1998, 322-324
  • [5] DomekS., Robust predictive model following control for uncertain nonlinear systems, Proceedings of the 8th IEEE Conf. on Methods and Models in Automation and Robotics, Szczecin 2002, 787-792.
  • [6] Esref EskinatS. H. J., LuybenW. L., Use of Hammerstein models in 'Identification of nonlinearsystems, AIChE, Vol. 37, No. 2, 1991,255-268.
  • [7] GomezJ. C., BAEYENS E., Subspace Identification of multivariable Hammerstein and Wiener models, Proceedings of the 15th Triennial World Congress, Barcelona 2002.
  • [8] Greblicki W., Pawlak M., Cascade nonlinear system identification by a nonparametric method,Int. J. of System Science, Vol. 25, 1994, 129-153.
  • [9] Grimble M. J., OrdysA. W., Predictive control design systems with stale dependent non­linearities, Proceedings of the SIAM Conf. on Control and Its Applications, San Diego 2001.
  • [10] Grimble M. J., OrdysA. W., Nonlinear predictive control for manufacluring and robotic applications, Proceedings of the 7th IEEE Conf. on Methods and Models in Automation and Robotics, Międzyzdroje 2001,579-592.
  • [11] Lee Y. I., KouvaritakisB., CannonM., Constrained receding horizon predictive control for non­linear systems, Automatica, Vol. 38, 2002, 2093-2102.
  • [12] Maciejowski J. M., PredictWe Control with Constraints, Prentice Hall, 2002.
  • [13] Michalska H., MayneD., Robust receding horizon control of constrained nonlinear systems,Proceedings of the IEEE Transactions on Automatic Control, Vol. 38, 1993, 1623-1632.
  • [14] Mutha R. K., CllettW. R., PenlidisA., Nonlinear model-based predictive control of controlnonaffine systems, Automatica, Vol. 33, 1997, 907-913.
  • [15] Skoczowski S., DomekS., Robust model following PID control, Proceedings of the 14th Int. Conf. on System Science, Wrocław 2001, Vol. 2, 54-61.
  • [16] SkoczowskiS., DomekS„ PietrusewiczK., Model Following PID Control, Kybcrnetes, 2003, Vol. 32, No. 5/6,818-828.
  • [17] SUGIE T., OsukaK., Robust model following control with prescribed accuracy for uncertain nonlin­ear systems, Int. J. Control, 1993, Vol. 58, No. 5, 991-1009.
  • [18] Tatjewski P., Advanced control of industrial processes. Structures and algorithms. Akademicka Oficyna Wydawnicza ЕХ1Т, Warszawa 2002, (in Polish).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAT5-0009-0024
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