Book Chapter10.1016/S1570-7946(03)80463-7
A multiple models based predictive control strategy applied in polymerization reactor control
TL;DR: In this article, a generalized predictive controller design is proposed for a polymerization reactor, in which an isothermal free-radical polymerization of methyl methacrylate is carried out using azo-bis-isobutyronitrile as initiator and toluene as solvent.
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Abstract: By making use of the multiple models to predict the process outputs in future time instants, a generalized predictive controller design is developed in this paper. However, the resulting nonlinear optimization problem cannot be solved straightforwardly because the values of the weighting functions in the prediction horizon are dependent on the future values of the process outputs and inputs. To circumvent this problem, an iterative procedure is developed. The proposed design is illustrated by considering the control of a polymerization reactor, in which an isothermal free-radical polymerization of methyl methacrylate is carried out using azo-bis-isobutyronitrile as initiator and toluene as solvent.
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References
Generalized predictive control—Part I. The basic algorithm
TL;DR: A novel method—generalized predictive control or GPC—is developed which is shown by simulation studies to be superior to accepted techniques such as generalized minimum-variance and pole-placement and to be a contender for general self-tuning applications.
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Modeling and control of a nonlinear process based on the extended self-organizing map network
TL;DR: An improved algorithm for the ESOM network is developed by employing a competitive learning algorithm for data clustering in the self-organization phase and parametric constraints are formulated in the optimization phase to handle the stability of local models.
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•Book
Multiple Model Approaches to Modelling and Control
Roderick Murray-Smith,Tor Arne Johansen +1 more
- 01 Jan 1997
TL;DR: 1. Basic Principles: The Operating Regime Approach 2. Modelling: Fuzzy Set Methods for Local Modelling Identification 3. Modelled of Electrically Stimulated Muscle
Nonlinear model predictive control of a simulated multivariable polymerization reactor using second-order Volterra models
TL;DR: Two formulations of a nonlinear model predictive control scheme based on the second-order Volterra series model are presented and the first formulation determines the control action using successive substitution, and the second method directly solves a fourth-order nonlinear programming problem on-line.