Optimal codesign of nonlinear control systems based on a modified policy iteration method

Yu Jiang, Yebin Wang, Scott A. Bortoff, Zhong Ping Jiang

Research output: Contribution to journalArticle

Abstract

This brief studies the optimal codesign of nonlinear control systems: simultaneous design of physical plants and related optimal control policies. Nonlinearity of the optimal codesign problem could come from either a nonquadratic cost function or the plant. After formulating the optimal codesign into a nonconvex optimization problem, an iterative scheme is proposed in this brief by adding an additional step of system-equivalence-based policy improvement to the conventional policy iteration. We have proved rigorously that the closed-loop system performance can be improved after each step of the proposed policy iteration scheme, and the convergence to a suboptimal solution is guaranteed. It is also shown that under certain conditions, this additional policy improvement step can be conducted by solving a quadratic programming problem. The linear version of the proposed methodology is addressed in the context of linear quadratic regulator. Finally, the effectiveness of the proposed methodology is illustrated through the optimal codesign of a load-positioning system.

Original languageEnglish (US)
Article number7001716
Pages (from-to)409-414
Number of pages6
JournalIEEE transactions on neural networks and learning systems
Volume26
Issue number2
DOIs
StatePublished - Feb 1 2015

Keywords

  • Codesign
  • nonlinear systems
  • optimal control
  • policy iteration.

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence

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