Explicit NMPC Using mp-QP Approximations of mp-NLP

  • Alexandra GrancharovaEmail author
  • Tor Arne Johansen
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 429)


A numerical algorithm for approximate multi-parametric nonlinear programming (mp-NLP) is developed. The algorithm locally approximates the mp-NLP with a multi-parametric quadratic program (mp-QP). This leads to an approximate mp-NLP solution that is composed from the solution of a number of mp-QP solutions. The method allows approximate solutions to nonlinear optimization problems to be computed as explicit piecewise linear functions of the problem parameters. In control applications such as nonlinear constrained model predictive control this allows efficient online implementation in terms of an explicit piecewise linear state feedback without any real-time optimization.


Model Predictive Control Sequential Quadratic Programming Binary Search Tree Nonlinear Model Predictive Control Polyhedral Region 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Institute of System Engineering and RoboticsBulgarian Academy of SciencesSofiaBulgaria
  2. 2.Department of Engineering CyberneticsNorwegian University of Science and TechnologyTrondheimNorway

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