Modelling and implicit modelling for predictive control

There should be a synergy between model identification and the role of the model in control law design, however this is often ignored in the literature. For the case of a predictive control law, the potential for synergy is quite transparent. The means of utilizing this link are discussed and illustrated and in particular it is shown that a slightly different approach to modelling can support a predictive control design to a far greater extent than conventional methods.

[1]  Edoardo Mosca,et al.  Stable redesign of predictive control , 1992, Autom..

[2]  Edoardo Mosca,et al.  Performance improvements of self-tuning controllers by multistep horizons: The MUSMAR approach , 1984, Autom..

[3]  Joseph Bentsman,et al.  Minimax long range parameter estimation , 1994, Proceedings of 1994 33rd IEEE Conference on Decision and Control.

[4]  E. Mosca,et al.  ARX modeling of controlled ARMAX plants and LQ adaptive controllers , 1989 .

[5]  Manfred Morari,et al.  Model predictive control: Theory and practice - A survey , 1989, Autom..

[6]  Basil Kouvaritakis,et al.  Linear Quadratic Feasible Predictive Control , 1998, Autom..

[7]  B. Kouvaritakis,et al.  The benefits of implicit modelling for predictive control , 2000, Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187).

[8]  Giuseppe Casalino,et al.  On implicit modelling theory: Basic concepts and application to adaptive control , 1987, Autom..

[9]  J. A. Rossiter,et al.  Notes on Multi-Step Ahead Prediction Based on the Principle of Concatenation , 1993 .

[10]  S. Shah,et al.  Identification for long-range predictive control , 1991 .

[11]  Michael J. Grimble,et al.  H ∞ optimal multichannel linear deconvolution filters, predictors and smoothers , 1996 .

[12]  Håkan Hjalmarsson,et al.  For model-based control design, closed-loop identification gives better performance , 1996, Autom..

[13]  J. Rawlings,et al.  Infinite Horizon Linear Quadratic Control with Constraints , 1996 .

[14]  Michel Gevers,et al.  SPC: Subspace Predictive Control , 1999 .

[15]  Sirish L. Shah,et al.  Multiple Prediction Models for Long Range Predictive Control , 1999 .

[16]  Mark Rice,et al.  A numerically robust state-space approach to stable-predictive control strategies , 1998, Autom..

[17]  B. Kouvaritakis,et al.  Stable generalised predictive control: an algorithm with guaranteed stability , 1992 .

[18]  M. B. Zarrop,et al.  Book Review: Adaptive Optimal Control: the thinking man's GPC , 1991 .

[19]  Svante Gunnarsson,et al.  Iterative feedback tuning: theory and applications , 1998 .

[20]  M. Grimble Polynomial systems approach to optimal linear filtering and prediction , 1985 .