Modeling, Identification and Control (Apr 1992)

State-space predictive control

  • Jens G. Balchen,
  • Dag Ljungqvist,
  • Stig Strand

DOI
https://doi.org/10.4173/mic.1992.2.2
Journal volume & issue
Vol. 13, no. 2
pp. 77 – 112

Abstract

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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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