149,864 research outputs found

    Computing an Optimal Control Policy for an Energy Storage

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    We introduce StoDynProg, a small library created to solve Optimal Control problems arising in the management of Renewable Power Sources, in particular when coupled with an Energy Storage System. The library implements generic Stochastic Dynamic Programming (SDP) numerical methods which can solve a large class of Dynamic Optimization problems. We demonstrate the library capabilities with a prototype problem: smoothing the power of an Ocean Wave Energy Converter. First we use time series analysis to derive a stochastic Markovian model of this system since it is required by Dynamic Programming. Then, we briefly describe the "policy iteration" algorithm we have implemented and the numerical tools being used. We show how the API design of the library is generic enough to address Dynamic Optimization problems outside the field of Energy Management. Finally, we solve the power smoothing problem and compare the optimal control with a simpler heuristic control.Comment: Part of the Proceedings of the 6th European Conference on Python in Science (EuroSciPy 2013), Pierre de Buyl and Nelle Varoquaux editors, (2014

    Distributed Control with Low-Rank Coordination

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    A common approach to distributed control design is to impose sparsity constraints on the controller structure. Such constraints, however, may greatly complicate the control design procedure. This paper puts forward an alternative structure, which is not sparse yet might nevertheless be well suited for distributed control purposes. The structure appears as the optimal solution to a class of coordination problems arising in multi-agent applications. The controller comprises a diagonal (decentralized) part, complemented by a rank-one coordination term. Although this term relies on information about all subsystems, its implementation only requires a simple averaging operation

    Decision rules and information provision: monitoring versus manipulation

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    The paper focuses on the organization of institutions designed to resolve disputes between two parties, when some information is not veri…able and decision makers may have vested preferences. It shows that the choice of how much discretional power to grant to the decision maker and who provides the information are intrinsically related. Direct involvement of the interested parties in the supply of information enhances monitoring over the decision maker, although at the cost of higher manipulation. Thus, it is desirable when the decision maker is granted high discretion. On the contrary, when the decision maker has limited discretional power, information provision is better assigned to an agent with no direct stake. The analysis helps to rationalize some organizational arrangements that are commonly observed in the context of judicial and antitrust decision-makin

    Cluster-based feedback control of turbulent post-stall separated flows

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    We propose a novel model-free self-learning cluster-based control strategy for general nonlinear feedback flow control technique, benchmarked for high-fidelity simulations of post-stall separated flows over an airfoil. The present approach partitions the flow trajectories (force measurements) into clusters, which correspond to characteristic coarse-grained phases in a low-dimensional feature space. A feedback control law is then sought for each cluster state through iterative evaluation and downhill simplex search to minimize power consumption in flight. Unsupervised clustering of the flow trajectories for in-situ learning and optimization of coarse-grained control laws are implemented in an automated manner as key enablers. Re-routing the flow trajectories, the optimized control laws shift the cluster populations to the aerodynamically favorable states. Utilizing limited number of sensor measurements for both clustering and optimization, these feedback laws were determined in only O(10)O(10) iterations. The objective of the present work is not necessarily to suppress flow separation but to minimize the desired cost function to achieve enhanced aerodynamic performance. The present control approach is applied to the control of two and three-dimensional separated flows over a NACA 0012 airfoil with large-eddy simulations at an angle of attack of 99^\circ, Reynolds number Re=23,000Re = 23,000 and free-stream Mach number M=0.3M_\infty = 0.3. The optimized control laws effectively minimize the flight power consumption enabling the flows to reach a low-drag state. The present work aims to address the challenges associated with adaptive feedback control design for turbulent separated flows at moderate Reynolds number.Comment: 32 pages, 18 figure

    Optimal control for unitary preparation of many-body states: application to Luttinger liquids

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    Many-body ground states can be prepared via unitary evolution in cold atomic systems. Given the initial state and a fixed time for the evolution, how close can we get to a desired ground state if we can tune the Hamiltonian in time? Here we study this optimal control problem focusing on Luttinger liquids with tunable interactions. We show that the optimal protocol can be obtained by simulated annealing. We find that the optimal interaction strength of the Luttinger liquid can have a nonmonotonic time dependence. Moreover, the system exhibits a marked transition when the ratio τ/L\tau/L of the preparation time to the system size exceeds a critical value. In this regime, the optimal protocols can prepare the states with almost perfect accuracy. The optimal protocols are robust against dynamical noise.Comment: 4 pages, 4 figures, extended results on robustness, to appear in PR

    H2 Optimal Coordination of Homogeneous Agents Subject to Limited Information Exchange

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    Controllers with a diagonal-plus-low-rank structure constitute a scalable class of controllers for multi-agent systems. Previous research has shown that diagonal-plus-low-rank control laws appear as the optimal solution to a class of multi-agent H2 coordination problems, which arise in the control of wind farms. In this paper we show that this result extends to the case where the information exchange between agents is subject to limitations. We also show that the computational effort required to obtain the optimal controller is independent of the number of agents and provide analytical expressions that quantify the usefulness of information exchange

    A revised model of fluid transport optimization in Physarum polycephalum

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    Optimization of fluid transport in the slime mold Physarum polycephalum has been the subject of several modeling efforts in recent literature. Existing models assume that the tube adaptation mechanism in P. polycephalum's tubular network is controlled by the sheer amount of fluid flow through the tubes. We put forward the hypothesis that the controlling variable may instead be the flow's pressure gradient along the tube. We carry out the stability analysis of such a revised mathematical model for a parallel-edge network, proving that the revised model supports the global flow-optimizing behavior of the slime mold for a substantially wider class of response functions compared to previous models. Simulations also suggest that the same conclusion may be valid for arbitrary network topologies.Comment: To appear in Journal of Mathematical Biolog

    Optimal suppression of defect generation during a passage across a quantum critical point

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    The dynamics of quantum phase transitions are inevitably accompanied by the formation of defects when crossing a quantum critical point. For a generic class of quantum critical systems, we solve the problem of minimizing the production of defects through the use of a gradient-based deterministic optimal control algorithm. By considering a finite size quantum Ising model with a tunable global transverse field, we show that an optimal power law quench of the transverse field across the Ising critical point works well at minimizing the number of defects, in spite of being drawn from a subset of quench profiles. These power law quenches are shown to be inherently robust against noise. The optimized defect density exhibits a transition at a critical ratio of the quench duration to the system size, which we argue coincides with the intrinsic speed limit for quantum evolution.Comment: 5 pages, 4 figures. The first two authors contributed equally to this wor
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