An instrumental variable method for real-time identification of a noisy process

  • Authors:

  • P. C. Young

  • Affiliations:

  • Control Group, Department of Engineering, University of Cambridge, England

  • Venue:
  • Automatica (Journal of IFAC)
  • Year:
  • 1970

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Abstract

The problem of identifying a dynamic process from its normal operating data has received considerable attention in recent years. The various techniques developed range from largely deterministic procedures to sophisticated statistical methods based on the results of optimal estimation theory. The instrumental variable (IV) technique outlined in this paper is intended as a compromise between these two extremes; it has a basis in classical statistical estimation theory, but does not require a priori information on the signal and noise statistics. The paper describes an IV approach to the problem of identifying a linear process described by a differential equation model and outlines the development of a simple digital recursive estimation algorithm. It also discusses briefly how the choice of input signal and the form of the mathematical model can affect the identifiability of a process. Finally, a number of representative experimental results are included both to demonstrate the practical feasibility of this particular approach to process identification, and to show that it can be used to estimate either time invariant or slowly variable process parameters.