NDLI: A new approach to stochastic adaptive control

Content Provider	IEEE Xplore Digital Library
Author	Meyn, S.P. Caines, P.E.
Copyright Year	1986
Description	Author affiliation: McGill University, Montré, Canada (Meyn, S.P.) \|\| McGill University, Montrél, Canada (Caines, P.E.)
Abstract	The principal techniques used up to now for the analysis of stochastic adaptive control systems have been (i) super-martingale (often called stochastic Lyapunov) methods and (ii) methods relying upon the strong consistency of some parameter estimation scheme. Optimal stochastic control and filtering methods have also been employed. Although there have been some successes, the extension of these techniques to a broad class of adptive control problems, including the case of time varying parameters, has been difficult. In this paper a new approach is adopted: If an underlying Markovian state space system for the controlled process is available, and if this process possesses stationary transition probabilities, then the powerful ergodic theory of Markov processes may be applied. Subject to technical conditions one may deduce (amongst other facts) (i) the existence of an invariant measure µ¿ for the process and (ii) the convergence almost surely of the sample averages of a function of the state process (and of its expectation) to its conditional expectation [µ¿] with respect to a sub-¿-field of invariant sets ¿I. The technique is illustrated by an application to a previously unsolved problem involving a linear system with unbounded random time varying parameters. Work suppoted by Canada NSERC Grant No.: 1329 and a UK SERC Visiting Research Fellowship.
Starting Page	1893
Ending Page	1897
File Size	368138
Page Count	5
File Format	PDF
DOI	10.1109/CDC.1986.267319
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1986-12-10
Publisher Place	Greece
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Stochastic processes Adaptive control Stochastic systems Parameter estimation Optimal control Filtering State-space methods Process control Control systems Markov processes
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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