An Instrumental Variable Method for Real-Time Identification of a Noisy Process.
NAVAL WEAPONS CENTER CHINA LAKE CA
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The problem of real-time process parameter estimation from 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 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 the approach to the problem and outlines the development of the simple digital recursive estimation algorithm. It also discusses 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 to demonstrate the practical feasibility of this particular approach to process identification. Author
- Statistics and Probability