Maximum a posteriori parameter estimation in large-scale systems

✍ Scribed by P. Chemouil; M.R. Katebi; D. Sastry; M.G. Singh

• Publisher: Elsevier Science
• Year: 1981
• Tongue: English
• Weight: 470 KB
• Volume: 17
• Category: Article
• ISSN: 0005-1098
• DOI: 10.1016/0005-1098(81)90072-8

✦ Synopsis

Maximum principle; large-scale systems; parameter estimation, iterative methods; boundary value problems.

Abstractmln this paper we examine the use of the maximum a posteriori (MAP) approach for parameter estimation in large-scale interconnected dynamical systems. We examine both the suboptimal approach of Sage and the optimal approaches which arise on solving within a multi-level structure the resulting nonlinear two point boundary value problem. In particular we consider two optimal methods i.e. the costate prediction method and the state estimation approach of Chen and Perils as applied to parameter estimation. We illustrate the approaches on a simple example which is used as a bench mark problem for purposes of comparison of the numerical efficiency of the various techniques.