Dynamic programming and suboptimal control: A survey from ADP to MPC

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172 Scopus citations

Abstract

We survey some recent research directions within the field of approximate dynamic programming, with a particular emphasis on rollout algorithms and model predictive control (MPC). We argue that while they are motivated by different concerns, these two methodologies are closely connected, and the mathematical essence of their desirable properties (cost improvement and stability, respectively) is couched on the central dynamic programming idea of policy iteration. In particular, among other things, we show that the most common MPC schemes can be viewed as rollout algorithms and are related to policy iteration methods. Furthermore, we embed rollout and MPC within a new unifying suboptimal control framework, based on a concept of restricted or constrained structure policies, which contains these schemes as special cases.

Original languageEnglish (US)
Pages (from-to)310-334
Number of pages25
JournalEuropean Journal of Control
Volume11
Issue number4-5
DOIs
StatePublished - 2005
Externally publishedYes

Keywords

  • Dynamic programming
  • Model predictive control
  • Rollout algorithm
  • Stochastic optimal control

ASJC Scopus subject areas

  • Engineering(all)

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