International Journal of Applied Mathematics and Computer Science (Jun 2020)

A linear programming methodology for approximate dynamic programming

  • Díaz Henry,
  • Sala Antonio,
  • Armesto Leopoldo

DOI
https://doi.org/10.34768/amcs-2020-0028
Journal volume & issue
Vol. 30, no. 2
pp. 363 – 375

Abstract

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The linear programming (LP) approach to solve the Bellman equation in dynamic programming is a well-known option for finite state and input spaces to obtain an exact solution. However, with function approximation or continuous state spaces, refinements are necessary. This paper presents a methodology to make approximate dynamic programming via LP work in practical control applications with continuous state and input spaces. There are some guidelines on data and regressor choices needed to obtain meaningful and well-conditioned value function estimates. The work discusses the introduction of terminal ingredients and computation of lower and upper bounds of the value function. An experimental inverted-pendulum application will be used to illustrate the proposal and carry out a suitable comparative analysis with alternative options in the literature.

Keywords