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AIAA Science and Technology (SciTech) Forum and Exposition

作者： Baker, Nicholas F. Stanley, Andrew P. J. Thomas, Jared J. Nine, Andrew Dykes, Katherine Brigham Young Univ Dept Mech Engn 360 EB Provo UT 84602 USA Natl Renewable Energy Lab Natl Wind Technol Ctr 15013 Denver West Pkwy Golden CO 80401 USA

ISBN: (数字)9781624105784

ISBN: (纸本)9781624105784

This paper presents the results of two case studies regarding the wind farm layout optimization problem. We asked members of the computational optimization and wind communities to take part in the studies that we designed. Nine individuals participated. Case study 1 considered variations in optimization strategies for a given simple Gaussian wake model. Participants were provided with a wake model that outputs annual energy production (AEP) for an input set of wind turbine locations. Participants used an optimization method of their choosing to find an optimal wind farm layout. Case study 2 looked at trade-offs in performance resulting from variation in both physics model and optimization strategy. For case study 2, participants calculated AEP using a wake model of their choice while also using their chosen optimization method. Participants then used their wake model to calculate the AEP of all other participants' optimized layouts. Results for case study 1 show that the best optimal wind farm layouts in this study were achieved by participants who used gradient-based optimization methods. A front-runner emerged with the Sparse Nonlinear OPTimizer plus Wake Expansion Continuation (SNOPT+WEC) optimization method, which consistently discovered the highest submitted AEP. For case study 2, two participants found a similar layout that was judged to be superior by all five participants. It is unclear if the better solution resulted from an improved optimization process, or a wake model that was more amenable to optimization.

关键词： sequential quadratic programming Wind Turbine Wakes Energy Production Sparse Nonlinear Optimizer Direct Numerical Simulation FORTRAN Turbulence Intensity Reynolds Averaged Navier Stokes Gradient Free Optimization Freestream Velocity

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A Robust Frequency Control Technique for Wind Power Conversion with Two-Level Structure Predictive Method

A Robust Frequency Control Technique for Wind Power Conversi...

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International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM)

作者： Nademi, Hamed Soghomonian, Zareh ABB Ind Automat Div N-0603 Oslo Norway CACI Int Inc 300 M St SE Washington DC 20003 USA

ISBN: (纸本)9781538649411

In modular and scalable matrix converters, which are deployed to interface the medium/high-power grids, there is huge interest to enhance the high computational burden of prevalent control schemes, such as model predictive control (MPC). In this paper, the operational performance of the Modular Multilevel Matrix Converter (M3C) is studied to transfer power generated by offshore wind farm and to interconnect the three-phase AC grid. The two-level structure control design is realized, of which a first-level predictive controller based on a Finite Control-Set Model Predictive Control (FCS-MPC) generates an initial controlled variables to regulate the converter branch voltages and currents. The second-level iterative controller is embedded into an integrated perturbation analysis and sequential quadratic programming (IPA-SQP) algorithm for handling uncertainty and updating weighting factors. The complete control scheme aiming to reduce sampling time and optimization of variable constraints, thus its optimality is proved through simulation analysis for a designed system with an equal or low operating frequency at the input or output AC systems for a M3C with 9-level line-to-line voltage.

关键词： Modular Multilevel Matrix Converter Model Predictive Control sequential quadratic programming Optimization problem Wind power

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Design Optimization of an Interior Permanent Magnet Synchronous Machine (IPMSM) for Electric Vehicle Application 5

Design Optimization of an Interior Permanent Magnet Synchron...

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5th IEEE International Conference on Renewable Energy Research and Applications (ICRERA)

作者： Turker, Harun TH Smart Grid Expertise & Consulting 2 Rue Pasteur F-38600 Fontaine France

ISBN: (纸本)9781509033881

The aim of this paper is to optimize the performances of an Interior Permanent Magnet Synchronous Machine (IPMSM) for an Electric Vehicle application. The originality of this work concerns the use of a Reluctance Network (RN) method which furnishes the harmonics of output parameters (i.e. torque and back-emf) and automatically generates the derivative of the model. Then, precise and very fast optimizations are performed own to gradient method as sequential quadratic programming (SQP). Results arc also compared to Finite Element Analysis (FEA) and several optimizations are presented. Finally, the proposed method helps engineers to have a better sense of machines behavior and to quickly optimize the geometry of their machines during preliminary Design Process.

关键词： Permanent Synchronous Machine Electric Vehicle Reluctance Network sequential quadratic programming Finite Element Analysis Design Process

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On a cellular developmental method for layout optimization via multi-fidelity analyses and the two-point topological derivative

On a cellular developmental method for layout optimization v...

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AIAA Aviation Forum and Exposition

作者： Kobayashi, Marcelo H. Canfield, Robert A. Kolonay, Raymond M. Univ Hawaii Manoa Dept Mech Engn 2540 Dole StHolmes Hall 302 Honolulu HI 96822 USA Virginia Polytech Inst & State Univ Kevin T Crofton Dept Aerosp & Ocean Engn Randolph HallRm 214460 Old Turner StMC 0203 Blacksburg VA 24061 USA Air Force Res Lab Multidisciplinary Sci & Technol Ctr 2210 8th StBldg 146Room 218 Wright Patterson AFB OH 45433 USA

ISBN: (数字)9781624106101

ISBN: (纸本)9781624106101

Handling multidisciplinary responses during structural topology optimization is important to a field that has grown rapidly in the last decade, spurred by additive manufacturing and 3D printing. The cellular division method for topological design is more general than conventional optimality criterion methods used most often in industrial structural topology design;however, it is a discrete approach that is daunting due to the curse of dimensionality. The innovative approach presented here formulates the design problem as a more tractable gradient-based one that exploits a new two-point topological derivative. Promising results are presented for benchmark test cases using the multi-fidelity approach using two-point topological derivatives to drive cellular development.

关键词： Topology Optimization Shape Optimization Cantilever Poisson's Ratio sequential quadratic programming Stress Distribution Energy Distribution Evolutionary Algorithm Structural Analysis Aspect Ratio

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Flying Complex Maneuvers with Model Predictive Path Integral Control

Flying Complex Maneuvers with Model Predictive Path Integral...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech Forum)

作者： Pravitra, Jintasit Theodorou, Evangelos A. Johnson, Eric N. Georgia Inst Technol Sch Aerosp Engn Atlanta GA 30332 USA Penn State Univ Dept Aerosp Engn University Pk PA 16802 USA

ISBN: (数字)9781624106095

ISBN: (纸本)9781624106095

The model predictive path integral (MPPI) control algorithm is applied to fixed-wing aircraft. Because MPPI imposes no restriction on the form of the cost function, arbitrarily complex maneuvers can be crafted through cost function design. MPPI works by propagating (thousands of) trajectories forward in time using random control inputs. This procedure is done in parallel using a graphics processing unit (GPU). The optimal control is computed by weight-averaging the controls from these trajectories (with each weight corresponds to the respective trajectory cost). A nonlinear wind-axes aircraft model is used in the MPPI propagation step. This choice of model offers two benefits. First, the model remains nonlinear which is appropriate for aggressive flights. Second, the model does not require parameters. Prediction error due to parametric uncertainty can be eliminated. We demonstrate our method in a simulated air racing scenario. Despite the simulated result, the real-time feasibility is validated because 1) the implementation is done in a flight-capable software framework, and 2) the simulation is done in a high fidelity flight dynamics simulator. We show that MPPI offers superior performances compared to a typical waypoint guidance. These include a smaller altitude drop in tight turns, a better ability to stay on course, and a lower maximum load factor.

关键词： Trajectory Optimization Fixed Wing Aircraft Air Racing Graphics Processing Unit Control Algorithm Flight Dynamics Model Predictive Control Autopilot sequential quadratic programming Parallel Computing Framework

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Optimal Cyclic Vertical Juggling Using 1-DoF Arm

Optimal Cyclic Vertical Juggling Using 1-DoF Arm

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IEEE International Conference on Robotics and Biomimetics (ROBIO)

作者： Akbarimajd, Adel Univ Mohaghegh Ardabili Dept Engn Ardebil Iran

ISBN: (纸本)9781424447749

Manipulation by juggling of an object by a 1-DoF prismatic arm is studied. The manipulation task is decomposed into two phases: accelerating phase and decelerating phas. The manipulation task is modeled as an optimization problem in order to get maximum flight while having minimum impact at catch time. The optimization problem is solved using sequential quadratic programming method and the results are verified by simulations in ADAMS.

关键词： sequential quadratic programming spiral arm Arm TWO-PHASE vertical

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Dynamic Joint Switching Point Configuration and Resource Allocation in TDD-OFDMA Wireless Networks

Dynamic Joint Switching Point Configuration and Resource All...

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54th Annual IEEE Global Telecommunications Conference (GLOBECOM)

作者： El-Hajj, Ahmad M. Dawy, Zaher Amer Univ Beirut Dept Elect & Comp Engn Beirut Lebanon

ISBN: (纸本)9781424492688

The development of the Time Division Duplexing (TDD) mode in next generation OFDMA-based wireless standards has brought some major advantages but at the same time raised several critical design requirements. Among others, the introduced flexibility in splitting resources between the uplink and downlink directions makes of the uplink/downlink switching point configuration a major design problem, especially that it is directly connected to other design aspects such as resource allocation and interference mitigation. In this paper, we propose a dynamic joint uplink/downlink resource allocation and switching point configuration algorithm. The proposed algorithm is channel-aware, traffic-aware, and service-aware. The resource allocation problem is formulated as an optimization problem that captures the different network parameters. Resulting instantaneous uplink and downlink rates are utilized in a dynamic estimation of the uplink and downlink time shares. A fast implementation using sequential quadratic programming is presented. Simulation results demonstrate the efficiency of the proposed approach in responding dynamically to varying network conditions and the improved performance when compared to fixed uplink/downlink switching point configurations.

关键词： Downlink Estimation Indexes Interference OFDM modulation Optimization Resource management Switches TDD-OFDMA wireless networks channel-aware downlink directions dynamic estimation dynamic joint switching point configuration dynamic joint uplink/downlink resource allocation major design problem next generation OFDMA-based wireless standards next generation networks optimization problem radio links radio networks resource allocation resource allocation problem sequential quadratic programming service-aware switching point configuration algorithm time division duplexing mode traffic-aware uplink directions uplink/downlink switching point configuration

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Optimal design of electronic components by mixed-integer nonlinear programming

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OPTIMIZATION AND ENGINEERING 2004年第3期5卷 271-294页

作者： Van De Braak, G Bünner, MJ Schittkowski, K Univ Bayreuth Dept Math D-95440 Bayreuth Germany Univ Munster Dept Math D-48149 Munster Germany EPCOS AG D-81617 Munich Germany

Cornputer-aided design optimization of electronic components is a powerful tool to reduce development costs on one hand and to improve the performance of (lie components on the other. In this paper, a mathematical model of an electronic filter is outlined. It depends oil certain parameters, some of then) of being continuous, others of integer type. The purpose of the paper is to introduce an extension of the well-known sequential quadratic programming (SQP) method to solve the mixed-integer programming problem (MINLP). It is assumed that the integer variables cannot be relaxed to real ones, that the integer range is sufficiently large, and that they possess some physical meaning so that they basically behave like continuous ones. The general idea is to combine all SQP step with a direct search cycle in the integer space, Hessian information is updated based on difference formulae at neighbored grid points. Numerical results are included to show the feasibility of the mixed-integer nonlinear programming code for academic test examples and in addition for the optimal design of an electronic filter.

关键词： electronic components mixed-integer nonlinear programming discrete optimization categorial variables sequential quadratic programming direct search method

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LOCAL CONVERGENCE OF A 2-PIECE UPDATE OF A PROJECTED HESSIAN MATRIX

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SIAM JOURNAL ON OPTIMIZATION 1994年第3期4卷 461-485页

作者： GURWITZ, C

The problem considered is that of minimizing a nonlinear function subject to a set of equality constraints. Recent research has focused on methods that solve such problems by recurring an approximation to second derivative information projected onto the tangent space of the constraints. The motivation for these methods is that only the projected matrix enters into the optimality conditions for the nonlinear problem and that the reduced matrix can be recurred by means of updates that maintain hereditary positive definiteness. However, such methods can achieve at best Local two-step Q-superlinear convergence. The algorithm presented here performs a two-piece update of a ''one-sided projected Hessian matrix:'' This method maintains one piece of the projected Hessian as a positive definite matrix and uses Broyden's method for updating the other piece. It is shown that if at least one of the updates is performed at each iteration, the method is locally one-step Q-superlinearly convergent.

关键词： CONSTRAINED OPTIMIZATION NONLINEAR programming PROJECTED HESSIAN REDUCED HESSIAN NEWTONS METHOD sequential quadratic programming

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Nonlinear semidefinite programming: sensitivity, convergence, and an application in passive reduced-order modeling

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MATHEMATICAL programming 2007年第2-3期109卷 581-611页

作者： Freund, Roland W. Jarre, Florian Vogelbusch, Christoph H. Univ Dusseldorf Inst Math D-40225 Dusseldorf Germany Univ Calif Davis Dept Math Davis CA 95616 USA

We consider the solution of nonlinear programs with nonlinear semidefiniteness constraints. The need for an efficient exploitation of the cone of positive semidefinite matrices makes the solution of such nonlinear semidefinite programs more complicated than the solution of standard nonlinear programs. This paper studies a sequential semidefinite programming (SSP) method, which is a generalization of the well-known sequential quadratic programming method for standard nonlinear programs. We present a sensitivity result for nonlinear semidefinite programs, and then based on this result, we give a self-contained proof of local quadratic convergence of the SSP method. We also describe a class of nonlinear semidefinite programs that arise in passive reduced-order modeling, and we report results of some numerical experiments with the SSP method applied to problems in that class.

关键词： nonlinear semidefinite programming sequential quadratic programming sensitivity reduced-order modeling positive realness

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