Robust optimal experiment design for system identification

  • Authors:

  • Cristian R. Rojas;James S. Welsh;Graham C. Goodwin;Arie Feuer

  • Affiliations:

  • School of Electrical Engineering and Computer Science, The University of Newcastle, Callaghan, NSW 2308, Australia;School of Electrical Engineering and Computer Science, The University of Newcastle, Callaghan, NSW 2308, Australia;School of Electrical Engineering and Computer Science, The University of Newcastle, Callaghan, NSW 2308, Australia;Department of Electrical Engineering, Technion - Israel Institute of Technology, Haifa 32000, Israel

  • Venue:
  • Automatica (Journal of IFAC)
  • Year:
  • 2007

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Abstract

This paper develops the idea of min-max robust experiment design for dynamic system identification. The idea of min-max experiment design has been explored in the statistics literature. However, the technique is virtually unknown by the engineering community and, accordingly, there has been little prior work on examining its properties when applied to dynamic system identification. This paper initiates an exploration of these ideas. The paper considers linear systems with energy (or power) bounded inputs. We assume that the parameters lie in a given compact set and optimise the worst case over this set. We also provide a detailed analysis of the solution for an illustrative one parameter example and propose a convex optimisation algorithm that can be applied more generally to a discretised approximation to the design problem. We also examine the role played by different design criteria and present a simulation example illustrating the merits of the proposed approach.