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2010•Industrial & Engineering Chemistry ResearchRequires access

Recent Advances in Explicit Multiparametric Nonlinear Model Predictive Control

Luis F. Domínguez, Efstratios N. Pistikopoulos

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Abstract

In this paper we present recent advances in multiparametric nonlinear programming (mp-NLP) algorithms for explicit nonlinear model predictive control (mp-NMPC). Three mp-NLP algorithms for NMPC are discussed, based on which novel mp-NMPC controllers are derived. The performance of the explicit controllers are then tested and compared in a simulation example involving the operation of a continuous stirred-tank reactor (CSTR).

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What this paper is about

In this paper we present recent advances in multiparametric nonlinear programming (mp-NLP) algorithms for explicit nonlinear model predictive control (mp-NMPC). Three mp-NLP algorithms for NMPC are discussed, based on which novel mp-NMPC controllers are derived. The performance of the explicit controllers are then tested and compared in a simulation example involving the operation of a continuous stirred-tank reactor (CSTR).

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OpenAlex reports 35 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In this paper we present recent advances in multiparametric nonlinear programming (mp-NLP) algorithms for explicit nonlinear model predictive control (mp-NMPC). Three mp-NLP algorithms for NMPC are discussed, based on which novel mp-NMPC controllers are derived. The performance of the explicit controllers are then tested and compared in a simulation example involving the operation of a continuous stirred-tank reactor (CSTR).

Key concepts: Continuous stirred-tank reactor, Model predictive control, Nonlinear system, Control theory (sociology), Nonlinear model, Computer science, Control (management), Nonlinear programming

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