Continuous-Time Constrained Least-Squares Algorithms for Recursive Parameter Estimation of Stochastic Linear Systems by a Stabilized Output Error Method

Udink ten Cate AJ (1985). Continuous-Time Constrained Least-Squares Algorithms for Recursive Parameter Estimation of Stochastic Linear Systems by a Stabilized Output Error Method. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-85-054

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Abstract

Discrete-time least-squares algorithms for recursive parameter estimation have continuous-time counterparts, which minimize a quadratic functional. The continuous-time algorithms can also include (in)equality constraints. Asymptotic convergence is demonstrated by means of Lyapunov methods. The constrained algorithms are applied in a stabilized output error configuration for parameter estimation in stochastic linear systems.

Item Type: Monograph (IIASA Working Paper)
Research Programs: System and Decision Sciences - Core (SDS)
Depositing User: IIASA Import
Date Deposited: 15 Jan 2016 01:55
Last Modified: 21 Jul 2016 22:19
URI: http://pure.iiasa.ac.at/2647

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