Lyapunov-Based Model Predictive Control

  • Panagiotis D. Christofides
  • Jinfeng Liu
  • David Muñoz de la Peña
Part of the Advances in Industrial Control book series (AIC)


In Chap. 2, some basic results on Lyapunov-based control, model predictive control and Lyapunov-based model predictive control of nonlinear systems are first reviewed and then two Lyapunov-based model predictive control (LMPC) designs for systems subject to data losses and time-varying measurement delays are presented. In order to provide guaranteed closed-loop stability results, the constraints that define the LMPC optimization problems as well as the implementation procedures are carefully designed to account for data losses (or asynchronous measurements) and time-varying measurement delays. The presented LMPC designs possess an explicit characterization of the closed-loop system stability region. Using a nonlinear chemical reactor example, it is demonstrated that the presented LMPC approaches are robust to data losses and measurement delays.


Stability Region Data Loss Continuously Stir Tank Reactor Prediction Horizon Measurement Delay 


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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  • Panagiotis D. Christofides
    • 1
  • Jinfeng Liu
    • 1
  • David Muñoz de la Peña
    • 2
  1. 1.Department of Chemical and Biomolecular EngineeringUniversity of California, Los AngelesLos AngelesUSA
  2. 2.Departamento de Ingeniería de Sistemas y AutomáticaUniversidad de SevillaSevillaSpain

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