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 -