Robust Optimal Control of Regular Languages

Jinbo Fu; Constantino M. Lagoa; Asok Ray

Robust Optimal Control of Regular Languages

Research output: Contribution to journal › Conference article › peer-review

Abstract

This paper presents an algorithm for robust optimal control of regular languages given uncertainty in event costs of a language measure that has been recently reported in literature. The performance index for the proposed robust optimal policy is obtained by combining the measure of the supervised plant language with uncertainty. The performance of a controller is represented by the language measure of supervised plant, minimized over the given range of event cost uncertainties. Synthesis of the robust optimal control policy requires at most n iterations, where n is the number of states of the deterministic finite state automaton (DFSA) model generated from the regular language of the open loop plant behavior. The computational complexity of control synthesis is polynomial in n.

Original language	English (US)
Pages (from-to)	3209-3214
Number of pages	6
Journal	Proceedings of the IEEE Conference on Decision and Control
Volume	4
State	Published - 2003
Event	42nd IEEE Conference on Decision and Control - Maui, HI, United States Duration: Dec 9 2003 → Dec 12 2003

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Modeling and Simulation
Control and Optimization

Cite this

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title = "Robust Optimal Control of Regular Languages",

abstract = "This paper presents an algorithm for robust optimal control of regular languages given uncertainty in event costs of a language measure that has been recently reported in literature. The performance index for the proposed robust optimal policy is obtained by combining the measure of the supervised plant language with uncertainty. The performance of a controller is represented by the language measure of supervised plant, minimized over the given range of event cost uncertainties. Synthesis of the robust optimal control policy requires at most n iterations, where n is the number of states of the deterministic finite state automaton (DFSA) model generated from the regular language of the open loop plant behavior. The computational complexity of control synthesis is polynomial in n.",

author = "Jinbo Fu and Lagoa, \{Constantino M.\} and Asok Ray",

note = "Funding Information: This paper was not presented at any IFAC meeting. This paper is recommended for publication in revised form by Associate Editor Xiren Cao under the direction of Editor Ian Petersen. This work has been supported in part by the Army Research Office under Grant No. DAAD19-01-1-0646, National Science Foundation under Grants Nos. ECS-9984260 and ANI-0125653, and NASA Glenn Research Center under Grant Nos. NAG3-2448 and NNC04GA49G. Copyright: Copyright 2008 Elsevier B.V., All rights reserved.; 42nd IEEE Conference on Decision and Control ; Conference date: 09-12-2003 Through 12-12-2003",

year = "2003",

language = "English (US)",

volume = "4",

pages = "3209--3214",

journal = "Proceedings of the IEEE Conference on Decision and Control",

issn = "0191-2216",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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TY - JOUR

T1 - Robust Optimal Control of Regular Languages

AU - Fu, Jinbo

AU - Lagoa, Constantino M.

AU - Ray, Asok

N1 - Funding Information: This paper was not presented at any IFAC meeting. This paper is recommended for publication in revised form by Associate Editor Xiren Cao under the direction of Editor Ian Petersen. This work has been supported in part by the Army Research Office under Grant No. DAAD19-01-1-0646, National Science Foundation under Grants Nos. ECS-9984260 and ANI-0125653, and NASA Glenn Research Center under Grant Nos. NAG3-2448 and NNC04GA49G. Copyright: Copyright 2008 Elsevier B.V., All rights reserved.

PY - 2003

Y1 - 2003

N2 - This paper presents an algorithm for robust optimal control of regular languages given uncertainty in event costs of a language measure that has been recently reported in literature. The performance index for the proposed robust optimal policy is obtained by combining the measure of the supervised plant language with uncertainty. The performance of a controller is represented by the language measure of supervised plant, minimized over the given range of event cost uncertainties. Synthesis of the robust optimal control policy requires at most n iterations, where n is the number of states of the deterministic finite state automaton (DFSA) model generated from the regular language of the open loop plant behavior. The computational complexity of control synthesis is polynomial in n.

AB - This paper presents an algorithm for robust optimal control of regular languages given uncertainty in event costs of a language measure that has been recently reported in literature. The performance index for the proposed robust optimal policy is obtained by combining the measure of the supervised plant language with uncertainty. The performance of a controller is represented by the language measure of supervised plant, minimized over the given range of event cost uncertainties. Synthesis of the robust optimal control policy requires at most n iterations, where n is the number of states of the deterministic finite state automaton (DFSA) model generated from the regular language of the open loop plant behavior. The computational complexity of control synthesis is polynomial in n.

UR - https://www.scopus.com/pages/publications/1542289790

UR - https://www.scopus.com/pages/publications/1542289790#tab=citedBy

M3 - Conference article

AN - SCOPUS:1542289790

SN - 0191-2216

VL - 4

SP - 3209

EP - 3214

JO - Proceedings of the IEEE Conference on Decision and Control

JF - Proceedings of the IEEE Conference on Decision and Control

T2 - 42nd IEEE Conference on Decision and Control

Y2 - 9 December 2003 through 12 December 2003

ER -

Robust Optimal Control of Regular Languages

Abstract

All Science Journal Classification (ASJC) codes

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