On constrained steady-state optimal control: Dynamic KKT controllers

Jokic, A.; Lazăr, Mircea; Bosch, P.P.J. van den

doi:10.1109/acc.2008.4587200

Cited by 2 publications

(1 citation statement)

References 21 publications

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“…Reference inputs for the physicallayer system are then derived from these optimization-based dynamical states. Since these controllers are formulated to dynamically seek the Karush-Kuhn-Tucker (KKT) conditions for optimality, they have been referred to as dynamic KKT controllers [150], [151].…”

Section: Coupling Between the Transient And Steady-state Timescalesmentioning

confidence: 99%

Power systems without fuel

Taylor

Dhople

Callaway

2016

Renewable and Sustainable Energy Reviews

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The finiteness of fossil fuels implies that future electric power systems may predominantly source energy from fuel-free renewable resources like wind and solar. Evidently, these power systems without fuel will be environmentally benign, sustainable, and subject to milder failure scenarios. Many of these advantages were projected decades ago with the definition of the soft energy path, which describes a future where all energy is provided by numerous small, simple, and diverse renewable sources. Here we provide a thorough investigation of power systems without fuel from technical and economic standpoints. The paper is organized by timescale and covers issues like the irrelevance of unit commitment in networks without large, fuelbased generators, the dubiousness of nodal pricing without fuel costs, and the need for new system-level models and control methods for semiconductor-based energy-conversion interfaces.

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Section: Coupling Between the Transient And Steady-state Timescalesmentioning

confidence: 99%

Power systems without fuel

Taylor

Dhople

Callaway

2016

Renewable and Sustainable Energy Reviews

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Optimal Steady-State Control for Linear Time-Invariant Systems

Lawrence

Nelson

Mallada

et al. 2018

2018 IEEE Conference on Decision and Control (CDC)

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We consider the problem of designing a feedback controller that guides the input and output of a linear timeinvariant system to a minimizer of a convex optimization problem. The system is subject to an unknown disturbance that determines the feasible set defined by the system equilibrium constraints. Our proposed design enforces the Karush-Kuhn-Tucker optimality conditions in steady-state without incorporating dual variables into the controller. We prove that the input and output variables achieve optimality in equilibrium and outline two procedures for designing controllers that stabilize the closed-loop system. We explore key ideas through simple examples and simulations. I . I N T R O D U C T I O NMany engineering systems must be operated at an "optimal" steady-state that minimizes operational costs. For example, the generators that supply power to the electrical grid are scheduled according to the solution of an optimization problem which minimizes the total production cost of the generated power [1]. This same theme of guiding system variables to optimizers emerges in other areas, such as network congestion management [2], [3], chemical processing [4], [5], and wind turbine power capture [6, Section 2.7], [7].Traditionally, the optimal steady-state set-points are computed offline in advance, and then controllers are used in real time to track the set-points. However, this two-step design method is inefficient if the set-points must be updated repeatedly and often. For instance, the increased use of renewable energy sources causes rapid fluctuations in power networks, which decreases the effectiveness of the separated approach due to the rapidly-changing optimal steady-state [8]. Furthermore, the two-step method is infeasible if unmeasurable disturbances change the optimal set-points. To continuously keep operational costs to a minimum, such systems should instead employ a controller that continuously solves the optimization problem and guides the system to an optimizer despite disturbances; we will call the problem of designing such a controller the optimal steady-state (OSS) control problem.The prevalence of the OSS control problem in applications has motivated much work on its solution for general system classes. In the extremum-seeking control approach to OSS

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On constrained steady-state optimal control: Dynamic KKT controllers

Cited by 2 publications

References 21 publications

Power systems without fuel

Power systems without fuel

Optimal Steady-State Control for Linear Time-Invariant Systems

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