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IEEE Annual Conference on Decision and control

作者： Scott Moura Jan Bendtsen Victor Ruiz Civil and Environmental Engineering University of California Berkeley CA 94720 USA Department of Electronic Systems Automation and Control Aalborg University 9210 Aalborg Denmark Department of Mechanical and Aerospace Engineering University of California San Diego La Jolla CA 92093-0411 USA

ISBN: (纸本)9781467357159

This paper develops methods for state estimation of aggregated thermostatically controlled loads (TCLs) in smart grids, via partial differential equation (PDE) techniques. TCLs include on/off controlled devices, such as heat pumps, HVAC systems, and deep freezers. control of aggregated TCLs provides a promising opportunity to mitigate the mismatch between power generation and demand, thus enhancing grid reliability and enabling renewable energy penetration. However, persistent communication between thousands of TCLs to a central server can be prohibitive. To this end, this paper focuses on designing a state estimation scheme for a PDE-based model of aggregated TCLs, thus reducing the required communication. First, a two-state linear hyperbolic PDE model for homogenous TCL populations is presented. This model is extended to heterogeneous populations by including a diffusive term. Next, a state observer is derived, which uses only measurements of how many TCLs turn on/off at any given time. The design is proven to be exponentially stable via backstepping techniques. Finally, the observer's properties are demonstrated via simulation examples. The estimator provides system-critical information for power system monitoring and control.

关键词： Smart grids load control State estimation Observers Power system measurements High Voltage Alternating Current systems exponential stability. grid reliability Power production

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Accuracy and decision time for sequential decision aggregation

Accuracy and decision time for sequential decision aggregati...

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作者： Dandach, Sandra H. Carli, Ruggero Bullo, Francesco Center for Control Dynamical Systems and Computation University of California at Santa Barbara Santa Barbara CA 93106 United States United Technologies Research Center East Hartford CT 06108 United States Department of Information Engineering University of Padova Padova 35131 Italy Department of Mechanical Engineering Center for Control Dynamical Systems and Computation University of California at Santa Barbara Santa Barbara CA 93106 United States

This paper studies prototypical strategies to sequentially aggregate independent decisions. We consider a collection of agents, each performing binary hypothesis testing and each obtaining a decision over time. We assume the agents are identical and receive independent information. Individual decisions are sequentially aggregated via a threshold-based rule. In other words, a collective decision is taken as soon as a specified number of agents report a concordant decision (simultaneous discordant decisions and no-decision outcomes are also handled). We obtain the following results. First, we characterize the probabilities of correct and wrong decisions as a function of time, group size, and decision threshold. The computational requirements of our approach are linear in the group size. Second, we consider the so-called fastest and majority rules, corresponding to specific decision thresholds. For these rules, we provide a comprehensive scalability analysis of both accuracy and decision time. In the limit of large group sizes, we show that the decision time for the fastest rule converges to the earliest possible individual time, and that the decision accuracy for the majority rule shows an exponential improvement over the individual accuracy. Additionally, via a theoretical and numerical analysis, we characterize various speed/accuracy tradeoffs. Finally, we relate our results to some recent observations reported in the cognitive information processing (CIP) literature. © 2011 IEEE.

关键词： Decision making

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Solar generation prediction using the ARMA model in a laboratory-level micro-grid

Solar generation prediction using the ARMA model in a labora...

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IEEE International Conference on Smart Grid Communications (SmartGridComm)

作者： Rui Huang Tiana Huang Rajit Gadh Na Li Smart Grid Energy Research Center Mechanical Engineering University of California Los Angeles USA Control and Dynamical Systems California Institute of Technology USA

The goal of this article is to investigate and research solar generation forecasting in a laboratory-level micro-grid, using the UCLA Smart Grid Energy Research Center (SMERC) as the test platform. The article presents an overview of the existing solar forecasting models and provides an evaluation of various solar forecasting providers. The auto-regressive moving average (ARMA) model and the persistence model are used to predict the future solar generation within the vicinity of UCLA. In the forecasting procedures, the historical solar radiation data originates from SolarAnywhere. System Advisor Model (SAM) is applied to obtain the historical solar generation data, with inputting the data from SolarAnywhere. In order to validate the solar forecasting models, simulations in the System Identification Toolbox, Matlab platform are performed. The forecasting results with error analysis indicate that the ARMA model excels at short and medium term solar forecasting, whereas the persistence model performs well only under very short duration.

关键词： Forecasting Predictive models Mathematical model Data models Laboratories Solar radiation Satellites

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Online Learning Algorithm for Stackelberg Games in Problems with Hierarchy

Online Learning Algorithm for Stackelberg Games in Problems ...

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IEEE Annual Conference on Decision and control

作者： K. G. Vamvoudakis F. L. Lewis M. Johnson W. E. Dixon Center for Control Dynamical-systems and Computation (CCDC) University of California Automation and Robotics Research Institute University of Texas at Arlington NASA Ames Research Center Department of Mechanical and Aerospace Engineering University of Florida

ISBN: (纸本)9781467320658

This paper presents an online adaptive optimal control algorithm based on policy iteration reinforcement learning techniques to solve the continuous-time Stackelberg games with infinite horizon for linear systems. This adaptive optimal control method finds in real-time approximations of the optimal value and the Stackelberg-equilibrium solution, while also guaranteeing closed-loop stability. The optimal-adaptive algorithm is implemented as a separate actor/critic parametric network approximator structure for every player, and involves simultaneous continuous-time adaptation of the actor/critic networks. Novel tuning algorithms are given for the actor/critic networks. The convergence to the closed-loop Stackelberg equilibrium is proven and stability of the system is also guaranteed. A simulation example shows the effectiveness of the new online algorithm.

关键词： Stackelberg games Hierarchical control problems adaptive optimal control Social Hierarchy Game theory e-learning infinite horizon Best value algorithms

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Risk-Mitigated Optimal Power Flow for Wind Powered Grids

Risk-Mitigated Optimal Power Flow for Wind Powered Grids

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American control Conference

作者： Emma Sjodin Dennice F. Gayme Ufuk Topcu School of Electrical Engineering at the Royal Institute of Technology SE-100 44 Stockholm Sweden Dept. of Mechanical Engineering at Johns Hopkins University Baltimore MD USA 21218 Control and Dynamical Systems at the California Institute of Technology Pasadena CA USA 91125

ISBN: (纸本)9781457710957

Increased penetration of renewable energy sources poses new challenges to the power grid. Grid integrated energy storage combined with fast-ramping conventional generation can help to address challenges associated with power output variability. This paper proposes a risk mitigating optimal power flow (OPF) framework to study the dispatch and placement of energy storage units in a power system with wind generators that are supplemented by fast-ramping conventional back-up generators. This OPF with storage charge/discharge dynamics is solved as a finite-horizon optimal control problem. Chance constraints are used to implement the risk mitigation strategy. The model is applied to case studies based on the IEEE 14 bus benchmark system. First, we study the scheduling of spinning reserves and storage when generation and loads are subject to uncertainties. The framework is then extended to investigate the optimal placement of storage across different network topologies. The results of the case studies quantify the need for storage and reserves as well as suggest a strategy for their scheduling and placement.

关键词： Case studies placement optimal load flow energy storage Wind Generators power systems grids Power flow Dispatching Renewable energy renewable energy sources Frameworks Storage Grates Energy storage devices

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Model fusion via a master fuzzy system with special application to engineering materials

Model fusion via a master fuzzy system with special applicat...

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作者： Zhang, Qian Mahfouf, Mahdi Yates, John R. Pinna, Christophe Panoutsos, George Boumaiza, Soufiene Greene, Richard J. De Leon, Luis Department of Automatic Control and Systems Engineering University of Sheffield Sheffield S1 3JD United Kingdom School of Mechanical Aerospace and Civil Engineering University of Manchester M60 1QD United Kingdom Department of Mechanical Engineering University of Sheffield Sheffield S1 3JD United Kingdom Institute of Production Engineering and Machine Tools Leibniz University Hannover Germany

ISBN: (纸本)9783902661937

To improve the modelling performance, one should either propose new modelling methodologies or make the best of existing models. In this paper, the study is concentrated on the latter solution, where a structure-free modelling paradigm is proposed to combine various modelling techniques in 'symbiosis' using a 'master fuzzy system'. This approach is shown to be able to include the advantages of different modelling techniques altogether by minimising efforts relating optimisation of final structure. The proposed approach is then successfully applied to predict machining induced residual stresses for aerospace alloy components as well as mechanical properties of heat-treated alloy steels. © 2011 IFAC.

关键词： Fuzzy systems

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Dynamic vehicle routing for robotic systems

Dynamic vehicle routing for robotic systems

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作者： Bullo, Francesco Frazzoli, Emilio Pavone, Marco Savla, Ketan Smith, Stephen L. Center for Control Dynamical Systems and Computation Department of Mechanical Engineering University of California in Santa Barbara Santa Barbara CA 93106 United States Laboratory for Information and Decision Systems Department of Aeronautics and Astronautics Massachusetts Institute of Technology Cambridge MA 02139 United States Jet Propulsion Laboratory California Institute of Technology Pasadena CA 91109 United States Laboratory for Information and Decision Systems Massachusetts Institute of Technology Cambridge MA 02139 United States Department of Electrical and Computer Engineering University of Waterloo Waterloo ON N2L 3G1 Canada

Recent years have witnessed great advancements in the science and technology of autonomy, robotics, and networking. This paper surveys recent concepts and algorithms for dynamic vehicle routing (DVR), that is, for the automatic planning of optimal multivehicle routes to perform tasks that are generated over time by an exogenous process. We consider a rich variety of scenarios relevant for robotic applications. We begin by reviewing the basic DVR problem: demands for service arrive at random locations at random times and a vehicle travels to provide on-site service while minimizing the expected wait time of the demands. Next, we treat different multivehicle scenarios based on different models for demands (e.g., demands with different priority levels and impatient demands), vehicles (e.g., motion constraints, communication, and sensing capabilities), and tasks. The performance criterion used in these scenarios is either the expected wait time of the demands or the fraction of demands serviced successfully. In each specific DVR scenario, we adopt a rigorous technical approach that relies upon methods from queueing theory, combinatorial optimization, and stochastic geometry. First, we establish fundamental limits on the achievable performance, including limits on stability and quality of service. Second, we design algorithms, and provide provable guarantees on their performance with respect to the fundamental limits. © 2011 IEEE.

关键词： Adaptive algorithms

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Model Fusion via a Master Fuzzy System with Special Application to engineering Materials

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IFAC Proceedings Volumes 2011年第1期44卷 11732-11737页

作者： Qian Zhang Mahdi Mahfouf John R. Yates Christophe Pinna George Panoutsos Soufiene Boumaiza Richard J. Greene Luis De Leon Department of Automatic Control and Systems Engineering The University of Sheffield Sheffield S1 3JD UK School of Mechanical Aerospace and Civil Engineering The University of Manchester M60 1QD UK Department of Mechanical Engineering The University of Sheffield Sheffield S1 3JD UK Institute of Production Engineering and Machine Tools Leibniz University Hannover Germany

Abstract To improve the modelling performance, one should either propose new modelling methodologies or make the best of existing models. In this paper, the study is concentrated on the latter solution, where a structure-free modelling paradigm is proposed to combine various modelling techniques in ‘symbiosis’ using a ‘master fuzzy system'. This approach is shown to be able to include the advantages of different modelling techniques altogether by minimising efforts relating optimisation of final structure. The proposed approach is then successfully applied to predict machining induced residual stresses for aerospace alloy components as well as mechanical properties of heat-treated alloy steels.

关键词： Fuzzy modelling Prediction problems Material mechanical properties Steel

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Experimental demonstration of the dynamics and stability of a low reynolds number swimmer near a plane wall

Experimental demonstration of the dynamics and stability of ...

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作者： Zhang, Sebastian Or, Yizhar Murray, Richard M. Mechanical Engineering Department Clemson University SC 29634 United States Mechanical Engineering Department Technion - Israel Institute of Technology Haifa 32000 Israel Control and Dynamical Systems Department California Institute of Technology CA 91125 United States

ISBN: (纸本)9781424474264

The motion of microorganisms as well as of tiny robotic swimmers for biomedical applications is governed by low Reynolds number (Re) hydrodynamics, where viscous effects dominate and inertial effects are negligible. This paper presents experimental results that verify theoretical predictions of our recent work which analyzed the dynamics and stability of a low-Re swimmer near a plane wall. The experimental setup uses macro-scale swimmer prototypes which are propelled by rotating cylinders in highly viscous silicone oil. The motion is recorded by a video camera and position measurements are taken by an optical tracking system. The results show good qualitative agreement with our recent theoretical predictions. © 2010 AACC.

关键词： Video cameras

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Stochastic simulation of energy extraction with an optically controlled nano-electromechanical engine

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International Journal of Modelling and Simulation 2011年第2期31卷 134-142页

作者： Khoshnoud, Farbod Owhadi, Houman De Silva, Clarence W. Industrial Automation Laboratory Department of Mechanical Engineering University of British Columbia Vancouver BC V6T 1Z4 Canada Applied and Computational Mathematics California Institute of Technology 1200 E. California Blvd. Pasadena CA 91125 United States SOFTEK Services Ltd. 275 - 13500 Maycrest Way Richmond BC V6V 2N8 Canada Control and Dynamical Systems California Institute of Technology 1200 E. California Blvd. Pasadena CA 91125 United States

Stochastic simulation of a nano-electromechanical energy transducer is presented in this paper. This system acts like an engine with four transformations in each engine cycle that converts potential energy due to quantum vacuum fluctuation of the electromagnetic field, or Casimir effect, to electrical energy. The system is composed of an oscillating semiconductor boundary parallel to a fixed plate separated by vacuum. The effect of the Casimir pressure in this engine is controlled by changing the optical properties of the boundaries when they are exposed to radiation that alters the plasma frequency of the dielectric medium of the moving and stationary boundaries. The stochastic simulation presented in this paper demonstrates the efficiency of the device in achieving positive net energy and deals with uncertainties in modelling such as friction and noise in the system, thereby providing a realistic model. A Langevin equation, which describes the Brownian motion, is considered for stochastic simulation of the system. The work done by the Casimir force is carried out in an open path of energy conversion, and the external radiation input to this system is not a means of input energy;rather, it is a tool to vary the system parameters.

关键词： Engines

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