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

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/2702 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/2702 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/2702 archive 351 disk0/00/00/26/47 2016-01-15 01:55:58 2021-08-27 17:12:21 2016-01-15 01:55:58 monograph show 2 Udink ten Cate A.J. AL1313 Continuous-Time Constrained Least-Squares Algorithms for Recursive Parameter Estimation of Stochastic Linear Systems by a Stabilized Output Error Method pub iis_met prog_sds 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. 1985-09 published WP-85-054 WP-85-054 2463 public working_paper IIASA, Laxenburg, Austria 32 FALSE info:eu-repo/semantics/book