Linearized controller design for the output pdfs using square root based B-spline models

P. Kabore, H. Baki, H. Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents a linearized approach for the controller design of the shape of the output probability density functions for general stochastic systems. A square root approximation to the output probability density function is realized by a set of B-spline functions. This generally produces a nonlinear state space model for the weights of the B-spline approximation. A linearized model is therefore obtained and embedded into a performance function that measures the tracking error of the output probability density function with respect to a given distribution. By using this performance function as a Lyapunov function for the closed loop system, a feedback control input has been obtained which guarantees the closed loop stability and realizes the perfect tracking. The algorithm described in this paper has been tested on a simulated example and desired results have been achieved.

Original languageEnglish
Title of host publicationIFAC Proceedings Volumes (IFAC-PapersOnline)
EditorsGabriel Ferrate, Eduardo F. Camacho, Luis Basanez, Juan. A. de la Puente
PublisherIFAC Secretariat
Pages467-472
Number of pages6
Edition1
ISBN (Print)9783902661746
DOIs
StatePublished - 2002
Externally publishedYes
Event15th World Congress of the International Federation of Automatic Control, 2002 - Barcelona, Spain
Duration: Jul 21 2002Jul 26 2002

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
Number1
Volume35
ISSN (Print)1474-6670

Conference

Conference15th World Congress of the International Federation of Automatic Control, 2002
Country/TerritorySpain
CityBarcelona
Period07/21/0207/26/02

Funding

The author would like to thank the financial support from the UK EPSRC grant (GB/K97721).

FundersFunder number
Engineering and Physical Sciences Research CouncilGB/K97721

    Keywords

    • B-splines neural networks
    • Dynamic stochastic systems
    • Lyapunov stability theory
    • Probability density function

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