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Introduction

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Economic Model Predictive Control

Part of the book series: Advances in Industrial Control ((AIC))

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Abstract

The traditional approach for optimization and control of chemical processes is to employ a hierarchical approach. While this approach has been successfully deployed in industrial process control practice, a more integrated solution to optimization and control is needed for next-generation process operations. Economic model predictive control (EMPC) is a control technology that merges economic process optimization and control. A brief overview of the traditional hierarchical approach to optimization and control, key motivating factors for an integrated approach to optimization and control, and a high level discussion of the main difference between EMPC and more standard, i.e., tracking, model predictive control are provided in this chapter. Next, a few chemical process applications are presented. These applications are used in the subsequent chapters to study and analyze the various EMPC methods presented in this book. Finally, the objectives and the organization of this book are given.

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Authors and Affiliations

  1. Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, Los Angeles, CA, USA

    Matthew Ellis & Panagiotis D. Christofides

  2. Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB, Canada

    Jinfeng Liu

Authors
  1. Matthew Ellis
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  2. Jinfeng Liu
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  3. Panagiotis D. Christofides
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Correspondence to Matthew Ellis .

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Ellis, M., Liu, J., Christofides, P.D. (2017). Introduction. In: Economic Model Predictive Control. Advances in Industrial Control. Springer, Cham. https://doi.org/10.1007/978-3-319-41108-8_1

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  • DOI: https://doi.org/10.1007/978-3-319-41108-8_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-41107-1

  • Online ISBN: 978-3-319-41108-8

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