Adaptive Robust MPC: A Minimally-Conservative Approach

  • Darryl DeHaan
  • Martin Guay
  • Veronica Adetola
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 384)


Although there is great motivation for adaptive approaches to nonlinear model prediction control, few results to date can guarantee feasible adaptive stabilization in the presence of state or input constraints. By adapting a set-valued measure of the parametric uncertainty within the framework of robust nonlinear-MPC, the results of this paper establish such constrained adaptive stability. Furthermore, it is shown that the ability to account for future adaptation has multiple benefits, including both the ability to guarantee an optimal notion of excitation in the system without requiring dither injection, as well as the ability to incorporate substantially less conservative designs of the terminal penalty.


Model Predictive Control Adaptive Control Robust Control Nonlinear Systems 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Darryl DeHaan
    • 1
  • Martin Guay
    • 2
  • Veronica Adetola
    • 2
  1. 1.Praxair Inc.USA
  2. 2.Dept. Chemical EngineeringQueen’s UniversityKingstonCanada

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