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Adaptive Quasi-Decentralized MPC of Networked Process Systems

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Book cover Distributed Model Predictive Control Made Easy

Part of the book series: Intelligent Systems, Control and Automation: Science and Engineering ((ISCA,volume 69))

Abstract

This work presents a framework for quasi-decentralized model predictive control (MPC) design with an adaptive communication strategy. In this framework, each unit of the networked process system is controlled by a local control system for which the measurements of the local process state are available at each sampling instant. And we aim to minimize the cross communication between each local control system and the sensors of the other units via the communication network while preserving stability and certain level of control system performance. The quasi-decentralized MPC scheme is designed on the basis of distributed Lyapunov-based bounded control with sampled measurements and then the stability properties of each closed-loop subsystem are characterized. By using this obtained characterization, an adaptive communication strategy is proposed that forecasts the future evolution of the local process state within each local control system. Whenever the forecast shows signs of instability of the local process state, the measurements of the entire process state are transmitted to update the model within this particular control system to ensure stability; otherwise, the local control system will continue to rely on the model within the local MPC controller. The implementation of this theoretical framework is demonstrated using a simulated networked chemical process.

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Notes

  1. 1.

    A function \(\alpha (\cdot )\) is said to be of class \(\mathbf {K}\) if it is strictly increasing and \(\alpha (0)=0\).

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Authors and Affiliations

  1. University of California, Davis, California

    Y. Hu & N. H. El-Farra

Authors
  1. Y. Hu
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  2. N. H. El-Farra
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Corresponding author

Correspondence to Y. Hu .

Editor information

Editors and Affiliations

  1. Systems Engineering and Automation Dept, University of Seville, Seville, Spain

    José M. Maestre

  2. Dept of Marine & Transport Technology, Delft University of Technology, Delft, The Netherlands

    Rudy R. Negenborn

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© 2014 Springer Science+Business Media Dordrecht

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Hu, Y., El-Farra, N.H. (2014). Adaptive Quasi-Decentralized MPC of Networked Process Systems. In: Maestre, J., Negenborn, R. (eds) Distributed Model Predictive Control Made Easy. Intelligent Systems, Control and Automation: Science and Engineering, vol 69. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7006-5_13

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  • DOI: https://doi.org/10.1007/978-94-007-7006-5_13

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-7005-8

  • Online ISBN: 978-94-007-7006-5

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