MPC for Large-Scale Systems via Model Reduction and Multiparametric Quadratic Programming

Abstract

In this paper we present a methodology for achieving real-time control of systems modeled by partial differential equations. The methodology uses the explicit solution of the model predictive control (MPC) problem combined with model reduction. The explicit solution of the MPC problem leads to online MPC functionality without having to solve an optimization problem at each time step. Reduced-order models are derived using a goal-oriented, model-based optimization formulation that yields efficient models tailored to the application at hand. The approach is demonstrated for reduced-order output feedback control of a large-scale linear time invariant state space model of the discretized heat equation.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2006
Accession Number
ADA471269

Entities

People

  • J. T. Gravdahl
  • Karen Willcox
  • S. Hovland

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Computational Fluid Dynamics
  • Computational Science
  • Computer Programming
  • Differential Equations
  • Equations
  • Feedback
  • Fluid Dynamics
  • Mathematical Analysis
  • Model Predictive Control
  • Optimization
  • Partial Differential Equations
  • Quadratic Programming

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.

Technology Areas

  • Space
  • Space - Spacecraft Maneuvers