Nonlinear control of a batch polymerization reactor: An experimental study
Masoud Soroush,Costas Kravaris +1 more
TLDR
The experimental results show the excellent servo and regulatory performance of the nonlinear controller in the presence of modeling and observer initialization errors and active manipulated input constraints and its tuning is much easier.Abstract:
This work studies the experimental application of the globally linearizing control (GLC) method to a batch polymerization reactor. The nonlinear controller is implemented on a microcomputer to start up the reactor and then track a precalculated optimal temperature profile. The reactor temperature is controlled by manipulating two coordinated inputs: power to an electrical heat and cooling water flow rate. A reduced-order observer is used to estimate the concentration of initiator and monomer. Systematic tuning guidelines are proposed for the nonlinear control method. The experimental results show the excellent servo and regulatory performance of the nonlinear controller in the presence of modeling and observer initialization errors and active manipulated input constraints. Furthermore, in comparison to a conventional PID controller, the performance of the nonlinear controller is significantly superior, and its tuning is much easier.read more
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Journal ArticleDOI
Input-output linearizing control of constrained nonlinear processes
TL;DR: In this paper, an input-output linearization strategy for constrained nonlinear processes is proposed, which combines the computational simplicity of input output linearization and the constraint handling capability of model predictive control.
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Batch unit optimization with imperfect modelling: a survey
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Within-Batch and Batch-to-Batch Inferential-Adaptive Control of Semibatch Reactors: A Partial Least Squares Approach
TL;DR: An inferential control strategy that combines within-batch information from process variable trajectories and information from prior batches to control multivariate product quality properties in single-shot batches.
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The online use of first-principles models in process operations: Review, current status and future needs
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Control of a solution copolymerization reactor using multi-model predictive control
TL;DR: In this paper, a model predictive control algorithm based on multiple piecewise linear models is proposed to control a solution copolymerization reactor using a receding horizon scheme with a quasi-infinite horizon objective function which has finite and infinite horizon cost components.
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