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8th IET International Conference on Power Electronics, Machines and Drives (PEMD 2016)

作者： Andreas Lindner Haris Kurtović Ingo Hahn Electrical Drives and Machines University of Erlangen-Nuremberg Cauerstraße 9 D-91052 Germany

ISBN: (纸本)9781510825666

A detailed investigation of different pole shapes of a flux switching machine with a large air-gap (δ = 3 mm) compared to the machines outer diameter (D sa = 100 mm) is conducted by means of 2D finite element analysis. The rotor pole shape as well as the stator core is modelled using parametrized spline curves to improve the electromagnetic performance of the FSPM machine. During the design process, the main governing parameters of the machine are kept constant except the number of turns per phase which is adapted to the actual slot area. Additionally, an alternative optimization method is implemented using a combination of several parts of wellknown optimization algorithms and chaotic parameter generation. It is shown, that the proposed method is capable to increase the torque of the machine by more than 12 % which is in general not an easy task for this small machine.

关键词： Flux-switching permanent magnet machine Switched flux machine Large air-gap Spline shaped magnetic core Electromagnetic performance machine electromagnetic properties Stator cores AIR GAP pole shape Pole Revolution Number optimization algorithms

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Self-organized UAV traffic in realistic environments

Self-organized UAV traffic in realistic environments

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Csaba Viragh Mate Nagy Carlos Gershenson Gabor Vasarhelyi Biological Physics Department Eotvos University Budapest Hungary MTA-ELTE Statistical and Biological Physics Research Group Budapest Hungary IIMAS & C3 UNAM Mexico City Mexico

ISBN: (纸本)9781509037636

e investigated different dense multirotor UAV traffic simulation scenarios in open 2D and 3D space, under realistic environments with the presence of sensor noise, communication delay, limited communication range, limited sensor update rate and finite inertia. We implemented two fundamental self-organized algorithms: one with constant direction and one with constant velocity preference to reach a desired target. We performed evolutionary optimization on both algorithms in five basic traffic scenarios and tested the optimized algorithms under different vehicle densities. We provide optimal algorithm and parameter selection criteria and compare the maximal flux and collision risk of each solution and situation. We found that i) different scenarios and densities require different algorithmic approaches, i.e., UAVs have to behave differently in sparse and dense environments or when they have common or different targets;ii) a slower-is-faster effect is implicitly present in our models, i.e., the maximal flux is achieved at densities where the average speed is far from maximal;iii) communication delay is the most severe destabilizing environmental condition that has a fundamental effect on performance and needs to be taken into account when designing algorithms to be used in real life.

关键词： Three-dimensional displays Two dimensional displays Roads Trajectory Mathematical model Vehicles Robot sensing systems three-dimensional displays Manipulator sensing systems vehicle Road trajectory Mathematical Model Unmanned Aerial Vehicle drone honey bees communication range Environments collision risk optimization algorithms Average speed

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An optimisation algorithm for matching large scale databases on customers for improved characterisation of electricity consumption

An optimisation algorithm for matching large scale databases...

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Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion (MedPower 2016)

作者： Thibaut Barbier Robin Girard Nicolas Kong François-Pascal Neirac Georges Kariniotakis Elena Magliaro Centre for Processes Renewable Energies and Energy Systems (PERSEE) MINES ParisTech PSL - Research University Sophia Antipolis France Enedis Paris La Défense France

ISBN: (纸本)9781510836884

This paper presents a method that permits to match customer information from the French DSO Enedis and housing information from the French population census institute INSEE. Our method allows having a list of housings linked to each customer in order to add household and building information to customers. We show with our method improvements in predictions of aggregated load curve indicators compared to the traditional method that averages socio demographic indicators from housing information of the zone covered by measurements. Our results indicate that the proposed algorithm is able to capture efficiently the information of housings in some feeders. This permits to combine the databases of the DSO with external databases that exist from census or other processes. Enriching the information at the level of clients through the proposed automated way is a cost effective approach given the number of customers served by a DSO. This enhanced information can be then the basis to model, analyse and simulate demand in a bottom up approach which can be useful for planning purposes of the distribution networks.

关键词： power distribution planning optimisation power consumption power distribution planning optimization algorithms Domestic architecture digital storage oscilloscopes Power consumption customers Customer information electricity consumption Purchasing census External databases Power grids Database information

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Q-matrix Learning and DINA Model Parameter Estimation

Q-matrix Learning and DINA Model Parameter Estimation

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International Conference on Behavior, Economic and Socio-cultural Computing

作者： Yuan Sun Shiwei Ye Guiping Su Yi Sun National Institute of Informatics University of China Academy of Science

ISBN: (纸本)9781509061655

The DINA model is one of the most widely used models in cognitive and skills diagnosis, and several algorithms have been developed for estimating the model parameters. However, since the parameter space is very large and has a mix of binary variables, even medium-sized testing is extremely challenging. To make the model practical, a fast optimization algorithm for parameter estimation is needed. In this study, we converted the deterministic Q-matrix learning problem into a Boolean matrix factorization (BMF) problem and developed a recursive algorithm to find an approximate solution while solving the uncertainty parameters analytically using maximum likelihood estimation (MLE). We proved that the MLE is equivalent to the minimum information entropy of the DINA model. Simulation results demonstrated that our proposed algorithm converges rapidly to the optimal solution under suitable initial values of skill - item association and is insensitive to the initial values of the uncertainty parameters.

关键词： maximum likelihood estimation model parameters parameter space methods Recursive algorithms optimization algorithms optimal solution Parameter estimation BMF gene

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Kronecker Determinantal Point Processes 16

Kronecker Determinantal Point Processes

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Annual Conference on Neural Information Processing Systems

作者： Zelda Mariet Suvrit Sra Massachusetts Institute of Technology Cambridge MA 02139

ISBN: (纸本)9781510838819

Determinantal Point Processes (DPPs) are probabilistic models over all subsets a ground set of N items. They have recently gained prominence in several applications that rely on "diverse" subsets. However, their applicability to large problems is still limited due to O(N~3) complexity of core tasks such as sampling and learning. We enable efficient sampling and learning for DPPs by introducing KronDpp, a DPP model whose kernel matrix decomposes as a tensor product of multiple smaller kernel matrices. This decomposition immediately enables fast exact sampling. But contrary to what one may expect, leveraging the Kronecker product structure for speeding up DPP learning turns out to be more difficult. We overcome this challenge, and derive batch and stochastic optimization algorithms for efficiently learning the parameters of a KronDpp.

关键词： Learning orthogonality optimization algorithms Tensor products Sampling Probabilistic Model Speeding decomposition Seeds dipalmitoylphosphatidylserine matrices

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LOCAL REFINEMENT FOR 3D DEFORMABLE PARAMETRIC SURFACES

LOCAL REFINEMENT FOR 3D DEFORMABLE PARAMETRIC SURFACES

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IEEE International Conference on Image Processing

作者： Anais Badoual Daniel Schmitter Michael Unser Biomedical Imaging Group Ecole Polytechnique Federale de Lausanne (EPFL)

ISBN: (纸本)9781467399623

Biomedical image segmentation is an active field of research where deformable models have proved to be efficient. The geometric representation of such models determines their ability to approximate the shape of interest as well as the speed of convergence of related optimization algorithms. We present a new tensor-product parameterization of surfaces that offers the possibility of local refinement. The goal is to allocate additional degrees of freedom to the surface only where an increase in local detail is required. We introduce the possibility of locally increasing the number of control points by inserting basis functions at specific locations. Our approach is generic and relies on refinable functions which satisfy the refinement relation. We show that the proposed method improves brain segmentation in 3D MRI images.

关键词： Deformable model Parametric surface Refinable function Local refinement Segmentation Splines Deformable models splines (mathematics) Surfaces Degree of freedom field surveys optimization algorithms Probability image segmentation

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Residual Vibration Reduction of Flexible Joint Systems using a Frequency Domain Trajectory Planning Algorithm

Residual Vibration Reduction of Flexible Joint Systems using...

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IEEE Multi-Conference on Systems and Control

作者： Markus Ruf German Aerospace Center (DLR) Institute of System Dynamics and Control

ISBN: (纸本)9781509007561

Fast motions of systems with constrained flexible dynamics often lead to residual vibrations. Established methods for compensating those vibrations such as input-shaping, filtering and feed-forward methods are already available. However, those methods do not explicitly consider input-constraints. As a consequence, they cannot effectively reduce residual vibrations if input-constraints are violated. This depends on the trajectory they are applied on, which is generated by a trajectory planning algorithm. In this paper, a trajectory planning algorithm is introduced which incorporates a residual vibration compensation procedure within the algorithm. In order to minimize the trajectory's excitation of the resonant frequency, a cost function is defined in the frequency domain and input-constraints are considered in the optimization algorithm. Hence, suppression of residual vibrations for fast motions can be achieved. The algorithm is implemented and tested on a robotic manipulator.

关键词： residual vibration trajectory planning Frequency-domain analysis absorption of shock Vibration Robot Manipulator algorithms Flexible connections optimization algorithms Cost functions trajectory

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40 years FORM: Some new aspects?

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PROBABILISTIC ENGINEERING MECHANICS 2015年 42卷 71-77页

作者： Breitung, Karl Tech Univ Munich Engn Risk Anal Grp D-80333 Munich Germany

40 years ago Hasofer and Lind wrote their seminal paper [13] about FORM where they described an algorithm for finding the beta point. This algorithm, later in 1978 generalized by Rackwitz and Fiessler in [23] to include nonnormal random variables, is known as Hasofer-Lind-Rackwitz-Fiessler (HL-RF) algorithm and till now it is an important tool for reliability calculations. Here its relation with standard numerical optimization is explained. Further a simple method for computing the SORM factor is given and the connection of FORM/SORM with dimension reduction concepts is outlined. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Failure probability Structural reliability Dimension reduction FORM/SORM Modified HL-RF method optimization algorithms Reliability index

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Improved structures for data collection in static and mobile wireless sensor networks

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JOURNAL OF HEURISTICS 2015年第2期21卷 233-256页

作者： Crowcroft, Jon Segal, Michael Levin, Liron Univ Cambridge Comp Lab Cambridge CB2 3QG England Ben Gurion Univ Negev Dept Commun Syst Engn Beer Sheva Israel

In this paper we consider the problem of efficient data gathering in sensor networks for arbitrary sensor node deployments. The efficiency of the solution is measured by a number of criteria: total energy consumption, total transport capacity, latency and quality of the transmissions. We present a number of different constructions with various tradeoffs between aforementioned parameters. We provide theoretical performance analysis for our approaches, present their distributed implementation and discuss the different aspects of using each. We show that in many cases our output-sensitive approximation solution performs better than the currently known best results for sensor networks. We also consider our problem under the mobile sensor nodes environment, when the sensors have no information about each other. The only information a single sensor holds is its current location and future mobility plan. Our simulation results validate the theoretical findings.

关键词： Wireless sensor networks optimization algorithms Approximation guarantees Data gathering

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Closed-Loop Control of Variable Stiffness Actuated Robots via Nonlinear Model Predicative Control

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IEEE ACCESS 2015年 3卷 235-248页

作者： Zhakatayev, Altay Rubagotti, Matteo Varol, Huseyin Atakan Nazarbayev Univ Dept Robot & Mech Astana 010000 Kazakhstan

Variable stiffness actuation has recently attracted great interest in robotics, especially in areas involving a high degree of human-robot interaction. After investigating various design approaches for variable stiffness actuated (VSA) robots, currently the focus is shifting to the control of these systems. Control of VSA robots is challenging due to the intrinsic nonlinearity of their dynamics and the need to satisfy constraints on input and state variables. Contrary to the partially open-loop state-of-the-art approaches, in this paper, we present a close-loop control framework for VSA robots leveraging recent increases in computational resources and advances in optimization algorithms. In particular, we generate reference trajectories by means of open-loop optimal control, and track these trajectories via nonlinear model predictive control in a closed-loop manner. In order to show the advantages of our proposed scheme with respect to the previous (partially open-loop) ones, extensive simulation and real-world experiments were conducted using a two link planar manipulator for a ball throwing task. The results of these experiments indicate that the closed-loop scheme outperforms the partially open loop one due to its ability to compensate for model uncertainties and external disturbances, while satisfying the imposed constraints.

关键词： Robot manipulation variable stiffness actuation model predictive control optimization algorithms embedded optimization

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