Robust Optimal Control of Regular Languages

    Research output: Contribution to journalConference article

    9 Citations (Scopus)

    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 languageEnglish (US)
    Pages (from-to)3209-3214
    Number of pages6
    JournalProceedings of the IEEE Conference on Decision and Control
    Volume4
    StatePublished - Dec 1 2003

    Fingerprint

    Formal languages
    Regular Languages
    Robust Control
    Optimal Control
    Optimal Policy
    Uncertainty
    Synthesis
    Finite State Automata
    Costs
    Finite automata
    Control Policy
    Performance Index
    Computational complexity
    Computational Complexity
    Polynomials
    Controller
    Iteration
    Controllers
    Polynomial
    Range of data

    All Science Journal Classification (ASJC) codes

    • Control and Systems Engineering
    • Modeling and Simulation
    • Control and Optimization

    Cite this

    @article{fa96bb7da77746809c2003296a8a86e5,
    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 Manuel} and Asok Ray",
    year = "2003",
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    day = "1",
    language = "English (US)",
    volume = "4",
    pages = "3209--3214",
    journal = "Proceedings of the IEEE Conference on Decision and Control",
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    Robust Optimal Control of Regular Languages. / Fu, Jinbo; Lagoa, Constantino Manuel; Ray, Asok.

    In: Proceedings of the IEEE Conference on Decision and Control, Vol. 4, 01.12.2003, p. 3209-3214.

    Research output: Contribution to journalConference article

    TY - JOUR

    T1 - Robust Optimal Control of Regular Languages

    AU - Fu, Jinbo

    AU - Lagoa, Constantino Manuel

    AU - Ray, Asok

    PY - 2003/12/1

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    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.

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    M3 - Conference article

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    SP - 3209

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    JO - Proceedings of the IEEE Conference on Decision and Control

    JF - Proceedings of the IEEE Conference on Decision and Control

    SN - 0191-2216

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