Worst-case identification of nonlinear fading memory systems

✍ Scribed by Munther A. Dahleh; Eduardo D. Sontag; David N.C. Tse; John N. Tsitsiklis

• Publisher: Elsevier Science
• Year: 1995
• Tongue: English
• Weight: 786 KB
• Volume: 31
• Category: Article
• ISSN: 0005-1098
• DOI: 10.1016/0005-1098(94)00131-2

✦ Synopsis

In this paper, the problem of asymptotic identification for fading memory systems in the presence of bounded noise is studied. For any experiment, the worst-case error is characterized in terms of the diameter of the worst-case uncertainty set. Optimal inputs that minimize the radius of uncertainty are studied and characterized. Finally, a convergent algorithm that does not require knowledge of the noise upper bound is furnished. The algorithm is based on interpolating data with spline functions, which are shown to be well suited for identification in the presence of bounded noise-more so than other basis functions such as polynomials. 1979), but recently there have also been some results in worst-case settings (Kacewicz and Milanese., 1992; Makila, 1991). Related work on the worst-case identification problem *