New methods for optimal control and filtering of singularly perturbed linear discrete stochastic systems

Myo Taeg Lim, Z. Gajic, X. Shen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

In this paper the algebraic regulator and filter Riccati equations of singularly perturbed discrete-time control systems are completely and exactly decomposed into reduced-order continuous-time algebraic Riccati equations corresponding to the slow and fast time scales. In addition, the optimal global Kalman filter is decomposed into pure-slow and pure-fast local optimal filters both driven by the system measurements and the system optimal control input. It is shown that these two filters can be implemented independently in the different time scales. As a result, the optimal linear-quadratic Gaussian control problem for singularly perturbed linear discrete systems takes the complete decomposition and parallelism between pure-slow and pure-fast filters and controllers.

Original languageEnglish
Title of host publicationProceedings of the American Control Conference
Pages534-538
Number of pages5
Volume1
Publication statusPublished - 1995
Externally publishedYes
EventProceedings of the 1995 American Control Conference. Part 1 (of 6) - Seattle, WA, USA
Duration: 1995 Jun 211995 Jun 23

Other

OtherProceedings of the 1995 American Control Conference. Part 1 (of 6)
CitySeattle, WA, USA
Period95/6/2195/6/23

ASJC Scopus subject areas

  • Control and Systems Engineering

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  • Cite this

    Lim, M. T., Gajic, Z., & Shen, X. (1995). New methods for optimal control and filtering of singularly perturbed linear discrete stochastic systems. In Proceedings of the American Control Conference (Vol. 1, pp. 534-538)