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“State-space predictive control”

Authors: Jens G. Balchen, Dag Ljungquist and Stig Strand,
Affiliation: NTNU, Department of Engineering Cybernetics
Reference: 1992, Vol 13, No 2, pp. 77-112.

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Keywords: Predictive control, state-space methods, non-linear control system, optimal control, iterative methods, on-line operation, catalytic cracking

Abstract: This paper deals with a predictive control strategy based on state-space models. Important issues concerning inherent model identification and optimal control computation are briefly discussed. Predictive control relies heavily on a model with satisfactory predictive capabilities. An off-line identification procedure must be accomplished to obtain a proper model structure and a parameter set, which is required for on-line adjustment. The control calculation is based on a general performance index and parameterization of the control variables in a nonlinear model, which includes the relevant constraints. This results in a finite-dimensional optimization problem which can be repetitively solved on-line. Simulation studies on two very different, typical industrial processes are presented. The simulations show that this MPC technique offers a major improvement in the control of many industrial processes.

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DOI forward links to this article:
  [1] David Di Ruscio (2013), doi:10.4173/mic.2013.3.2
  [2] J.A. Sørlie (1994), doi:10.1016/S1474-6670(17)47800-1


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BibTeX:
@article{MIC-1992-2-2,
  title={{State-space predictive control}},
  author={Balchen, Jens G. and Ljungquist, Dag and Strand, Stig},
  journal={Modeling, Identification and Control},
  volume={13},
  number={2},
  pages={77--112},
  year={1992},
  doi={10.4173/mic.1992.2.2},
  publisher={Norwegian Society of Automatic Control}
};

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