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    Linear Quadratic Regulator for Delayed Systems Using the Hamiltonian Approach and Exact Closed-Loop Poles for First-Order Systems

    Source: Journal of Dynamic Systems, Measurement, and Control:;2023:;volume( 145 ):;issue: 007::page 71002-1
    Author:
    Shaik, Junaidvali
    ,
    Vyasarayani, C. P.
    ,
    Chatterjee, Anindya
    DOI: 10.1115/1.4062439
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: We consider the linear quadratic regulator (LQR) for linear constant-coefficient delay differential equations (DDEs) with multiple delays. The Hamiltonian approach is used instead of an algebraic Riccati partial differential equation. Two coupled DDEs governing the state and control input are derived using the calculus of variations. This coupled system, with infinitely many roots in both left and right half-planes, defines a boundary value problem. Its left half-plane roots are the exact closed-loop poles of the controlled system. These closed-loop poles have not been used to compute the optimal feedback before. Here, the distributed delay kernel that yields exactly those poles is first computed using an eigenfunction expansion. Increasing the number of terms in the truncated expansion yields a highly oscillatory kernel. However, the oscillatory kernel's antiderivative converges to a piecewise smooth function on the delay interval plus a Dirac delta function at zero. Discontinuities in the kernel coincide with discrete delay values in the original DDE. Using this insight, a fitted piecewise polynomial kernel matches the exact closed-loop poles very well. The twofold contribution of the Hamiltonian approach is thus clarity on the form of the feedback kernel as well as the exact closed-loop poles. Subsequently, the fitted piecewise polynomial kernel can be used for a much simpler control calculation. The polynomial coefficients can be fitted by solving a few simultaneous linear equations. Two detailed numerical examples of the LQR for DDEs, one with two delays and one with three delays, show excellent results.
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      Linear Quadratic Regulator for Delayed Systems Using the Hamiltonian Approach and Exact Closed-Loop Poles for First-Order Systems

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4294203
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    contributor authorShaik, Junaidvali
    contributor authorVyasarayani, C. P.
    contributor authorChatterjee, Anindya
    date accessioned2023-11-29T18:32:10Z
    date available2023-11-29T18:32:10Z
    date copyright5/25/2023 12:00:00 AM
    date issued5/25/2023 12:00:00 AM
    date issued2023-05-25
    identifier issn0022-0434
    identifier otherds_145_07_071002.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4294203
    description abstractWe consider the linear quadratic regulator (LQR) for linear constant-coefficient delay differential equations (DDEs) with multiple delays. The Hamiltonian approach is used instead of an algebraic Riccati partial differential equation. Two coupled DDEs governing the state and control input are derived using the calculus of variations. This coupled system, with infinitely many roots in both left and right half-planes, defines a boundary value problem. Its left half-plane roots are the exact closed-loop poles of the controlled system. These closed-loop poles have not been used to compute the optimal feedback before. Here, the distributed delay kernel that yields exactly those poles is first computed using an eigenfunction expansion. Increasing the number of terms in the truncated expansion yields a highly oscillatory kernel. However, the oscillatory kernel's antiderivative converges to a piecewise smooth function on the delay interval plus a Dirac delta function at zero. Discontinuities in the kernel coincide with discrete delay values in the original DDE. Using this insight, a fitted piecewise polynomial kernel matches the exact closed-loop poles very well. The twofold contribution of the Hamiltonian approach is thus clarity on the form of the feedback kernel as well as the exact closed-loop poles. Subsequently, the fitted piecewise polynomial kernel can be used for a much simpler control calculation. The polynomial coefficients can be fitted by solving a few simultaneous linear equations. Two detailed numerical examples of the LQR for DDEs, one with two delays and one with three delays, show excellent results.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleLinear Quadratic Regulator for Delayed Systems Using the Hamiltonian Approach and Exact Closed-Loop Poles for First-Order Systems
    typeJournal Paper
    journal volume145
    journal issue7
    journal titleJournal of Dynamic Systems, Measurement, and Control
    identifier doi10.1115/1.4062439
    journal fristpage71002-1
    journal lastpage71002-13
    page13
    treeJournal of Dynamic Systems, Measurement, and Control:;2023:;volume( 145 ):;issue: 007
    contenttypeFulltext
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