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检索条件"任意字段=Conference on Simulation-Driven Modeling and Optimization"

共 1171 条记录，以下是521-530 订阅

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Dynamic Congestion Pricing for Ridesourcing Traffic: a simulation optimization Approach

Dynamic Congestion Pricing for Ridesourcing Traffic: a Simul...

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simulation Winter conference

作者： Qi Luo IOE Building University of Michigan Ann Arbor MI USA

ISBN: (数字)9781728132839

ISBN: (纸本)9781728120522

Despite the documented benefits of ridesourcing services, recent studies show that they can slow down traffic in the densest cities significantly. To implement congestion pricing policies upon those vehicles, regulators need to estimate the degree of congestion effect. This paper studies simulation-based approaches to address the two technical challenges arising from the representation of system dynamics and the optimization for congestion price mechanisms. To estimate the traffic state, we use a metamodel representation for traffic flow and a numerical method for data interpolation. To reduce the burden of replicating evaluation in stochastic optimization, we use a simulation optimization approach to compute the optimal congestion price. This data-driven approach can potentially be extended to solve large-scale congestion pricing problems with unobservable states.

关键词： optimization Pricing Computational modeling Traffic congestion Mathematical model Urban areas

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On Low-Fidelity Models for Variable-Fidelity simulation-driven Design optimization of Compact Wideband Antennas 22

On Low-Fidelity Models for Variable-Fidelity Simulation-Driv...

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22nd International Microwave and Radar conference (MIKON)

作者： Koziel, Slawomir Unnsteinsson, Sigmar D. Bekasiewicz, Adrian Reykjavik Univ Engn Optimizat & Modeling Ctr Reykjavik Iceland Gdansk Univ Technol Fac Elect Telecommun & Inf Gdansk Poland

ISBN: (纸本)9788394942113

The paper addresses simulation-driven design optimization of compact antennas involving variable-fidelity electromagnetic (EM) simulation models. Comprehensive investigations are carried out concerning selection of the coarse model discretization density. The effects of the low-fidelity model setup on the reliability and computational complexity of the optimization process are determined using a benchmark set of three ultra-wideband antennas designed for the best matching and for the minimum size. The optimization algorithm of choice is trust-region gradient search with low-fidelity model correction realized through frequency scaling and multiplicative output space mapping. The results indicate that appropriate low-fidelity model setup can be assessed using a correlation analysis based on the selected characteristic points of the antenna responses and sparsely allocated test designs, and the results are consistent across the considered benchmark set.

关键词： Antenna design EM-driven design variable-fidelity simulations design optimization low-fidelity models

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Realizing Learned Quadruped Locomotion Behaviors through Kinematic Motion Primitives

Realizing Learned Quadruped Locomotion Behaviors through Kin...

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IEEE International conference on Robotics and Automation (ICRA)

作者： Singla, Abhik Bhattaeharya, Shounak Dholakiya, Dhaivat Bhatnagar, Shalabh Ghosal, Ashitava Amrutur, Bharadwaj Kolathaya, Shishir IISc Robert Bosch Ctr Cyber Phys Syst Bangalore Karnataka India IISc Fac Comp Sci Automat Bengaluru India IISc Fac Mech Engn Bengaluru India IISc Fac Elect Sc Comp Engn Bengaluru India IISc Robert Bosch Ctr Cyber Phys Syst Bengaluru India

ISBN: (纸本)9781538660263

Humans and animals are believed to use a very minimal set of trajectories to perform a wide variety of tasks including walking. Our main objective in this paper is two fold 1) Obtain an effective tool to realize these basic motion patterns for quadrupedal walking, called the kinematic motion primitives (kMPs), via trajectories learned from deep reinforcement learning (D-RL) and 2) Realize a set of behaviors, namely trot, walk, gallop and bound from these kinematic motion primitives in our custom four legged robot, called the "Stoch". D-RL is a data driven approach, which has been shown to be very effective for realizing all kinds of robust locomotion behaviors, both in simulation and in experiment. On the other hand, kMPs are known to capture the underlying structure of walking and yield a set of derived behaviors. We first generate walking gaits from D-RL, which uses policy gradient based approaches. We then analyze the resulting walking by using principal component analysis. We observe that the kMPs extracted from PCA followed a similar pattern irrespective of the type of gaits generated. Leveraging on this underlying structure, we then realize walking in Stoch by a straightforward reconstruction of joint trajectories from kMPs. This type of methodology improves the transferability of these gaits to real hardware, lowers the computational overhead on-board, and also avoids multiple training iterations by generating a set of derived behaviors from a single learned gait.

关键词： Legged locomotion Trajectory Computational modeling Kinematics optimization Training

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Low-Cost simulation-driven Design of Broadband Rectifiers for Ambient RF Energy Harvesting

Low-Cost Simulation-Driven Design of Broadband Rectifiers fo...

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IEEE MTT-S International conference on Numerical Electromagnetic and Multiphysics modeling and optimization (NEMO)

作者： Bekasiewicz, Adrian Karataev, Tologon Koziel, Slawomir Gdansk Univ Technol Fac Elect Telecommun & Informat Gdansk Poland Reykjavik Univ Engn Optimizat & Modeling Ctr Reykjavik Iceland

ISBN: (纸本)9781538652046

A steady growth of ambient RF energy density associated with a rapid increase of the number of broadcasting devices stimulates the research on broadband harvesting circuits. Such circuits can be used as energy sources for low-power sensors or Internet-of-Things devices. On the other hand, dedicated design techniques for rectifiers are lacking which results in poor performance of existing circuits. Also, their design cost is high because it involves hybrid electromagnetic (EM) and harmonic balance (HB) simulations. In this work, we propose a novel design procedure for low-cost design of broadband rectifiers. The core component of the approach is a novel equivalent-circuit-based low-fidelity model which does not involve harmonic balance (HB) simulations. The model consists of a matching circuit loaded with the RF-to-DC converter block represented using the S-parameter matrix. The latter is obtained from a single HB simulation of the converter circuit. Inaccuracy of the model is reduced using appropriate correction techniques. At the first stage of the design process, the proposed model is optimized for minimization of the in-band reflection. At the second stage, a hybrid HB-EM-based tuning oriented towards maximization of the structure efficiency is carried out. The proposed approach is demonstrated using a novel broadband rectifier operating within 0.5 GHz to 3.5 GHz band. Numerical cost of the method is 80% lower compared to direct EM-HB-based optimization of the rectifier circuit.

关键词： broadband rectifiers simulation-driven design surrogate-based optimization constrained optimization equivalent circuit model

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Cyber-Physical Risk driven Routing Planning with Deep Reinforcement-Learning in Smart Grid Communication Networks

Cyber-Physical Risk Driven Routing Planning with Deep Reinfo...

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International Wireless Communications and Mobile Computing conference, IWCMC

作者： Zhuojun Jin Peng Yu Shao Yong Guo Lei Feng Fanqin Zhou Minxing Tao Wenjing Li Xue-Song Qiu Lei Shi State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China School of Computer Science Beijing University of Posts and Telecommunications Beijing China Carlow Institute of Technology Carlow Ireland

ISBN: (数字)9781728131290

ISBN: (纸本)9781728131306

In modern grid systems which is a typical cyber-physical System (CPS), information space and physical space are closely related. Once the communication link is interrupted, it will make a great damage to the power system. If the service path is too concentrated, the risk will be greatly increased. In order to solve this problem, this paper constructs a route planning algorithm that combines node load pressure, link load balance and service delay risk. At present, the existing intelligent algorithms are easy to fall into the local optimal value, so we chooses the deep reinforcement learning algorithm (DRL). Firstly, we build a risk assessment model. The node risk assessment index is established by using the node load pressure, and then the link risk assessment index is established by using the average service communication delay and link balance degree. The route planning problem is then solved by a route planning algorithm based on DRL. Finally, experiments are carried out in a simulation scenario of a power grid system. The results show that our method can find a lower risk path than the original Dijkstra algorithm and the Constraint-Dijkstra algorithm.

关键词： Planning Routing Delays Load modeling Smart grids Communication networks optimization

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Reliable EM-driven Design optimization of Miniaturized Rat-Race Couplers

Reliable EM-Driven Design Optimization of Miniaturized Rat-R...

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IEEE MTT-S International conference on Numerical Electromagnetic and Multiphysics modeling and optimization (NEMO)

作者： Koziel, Slawomir Kurgan, Piotr Reykjavik Univ Engn Optimizat & Modeling Ctr IS-101 Reykjavik Iceland Gdansk Univ Technol Fac Elect Telecommun & Informat PL-80233 Gdansk Poland

ISBN: (纸本)9781538652046

The paper addresses the problem of simulation-driven design of compact microwave couplers. The considered class of structures feature small-size layouts due to so-called compact microstrip resonant cells (CMRCs) incorporated as replacements for conventional transmission lines (TLs). CMRCs exhibit a slow-wave effect, which enables physical shortening of longitudinal circuit dimensions while retaining (within a certain frequency range) approximate electrical or wave parameters. The primary challenge in design of CMRC-based devices is proper adjustment of independent variables. Due to typically intricate CMRC geometries described by a large number of wide-ranged parameters (as compared to ordinary TLs), finding a reasonable starting point for subsequent design optimization poses considerable difficulties. Here, a novel algorithm for reliable CMRC optimization is proposed, which utilizes a combination of pattern search procedures, response features, and variable-fidelity EM simulations. As demonstrated through comprehensive case studies, the algorithm is capable of converging to a good solution regardless of the initial design. Furthermore, the CMRC optimizer is embedded in the design framework, which permits determining a minimum-size coupler with electrical performance that still satisfies design requirements imposed on the structure.

关键词： Compact structures EM optimization EM-driven design feature-based optimization pattern search rat-race couplers variable-fidelity EM models

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optimization-driven PRODUCT DEVELOPMENT TO SUPPORT DIGITAL TWIN CREATION ON THE SMALL UAV CASE STUDY 19

OPTIMIZATION-DRIVEN PRODUCT DEVELOPMENT TO SUPPORT DIGITAL T...

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Computer simulation conference

作者： Mikhail P. Gusev Sergei M. Nikolaev Anatolii P. Papulov Sergei D. Belov Daniil I. Padalitsa Ighor K. Uzhinsky Skolkovo Institute of Science and Technology Moscow Russia

Development of a complex product usually initiates with requirements and architecture design. Usually, for a complex product such as in the aerospace industry, the number of requirements is numerous and as one of the methodologies is Model-Based System Engineering (MBSE) that copes these challenges according to stakeholders needs. Models in MBSE have a different physics nature and specifically for the aerospace industry it can be approximations which are based on the statistical data or 1D models based on the physical equations. Despite MBSE approach solves a wide range of the issues on the high level of product development and helps to choose appropriate architecture, the technical requirements are usually not taken into account on that stage. An approach to deal with specified challenges is optimization-driven Product Development (ODPD) and the aim of this work is to demonstrate the leveraging of ODPD to the small Unmanned Aerial Vehicles (UAV) case study.

关键词： optimization-driven product development MBSE Small UAV

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A Data-driven Method for Computing Fixed-Structure Low-Order Controllers With H_∞ Performance 16

A Data-Driven Method for Computing Fixed-Structure Low-Order...

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European Control conference (ECC)

作者： Nicoletti, Achille Karimi, Alireza European Org Nucl Res CERN Technol Dept Geneva Switzerland Ecole Polytech Fed Lausanne Automat Control Lab Lausanne Switzerland

ISBN: (纸本)9783952426982

Recently, a new data-driven method for robust control with H-infinity performance has been proposed. This method is based on convex optimization and converges to the optimal performance when the controller order increases. However, for low-order controllers, the performance depends heavily on the choice of some fixed parameters that are used for convexifying the optimization problem. In this paper, several data-driven optimization algorithms are proposed to improve the solution for low-order controllers. A non-convex problem is solved (in a data-driven sense) where the parameters of a fixedstructure low-order controller are optimized;the solution to the problem guarantees the stability of the closed-loop system whilst ensuring robust performance. It is shown that by optimizing all of the controller parameters, the H-infinity performance for loworder controllers can be significantly improved. The simulation examples illustrate how the proposed method can be used to eliminate the sensitivity associated with the fixed parameters and optimize the system performance.

关键词： optimization Frequency response Transfer functions Convex functions Stability analysis Sensitivity Biological system modeling

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Data-driven Wind Farm optimization Incorporating Effects of Turbulence Intensity

Data-Driven Wind Farm Optimization Incorporating Effects of ...

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American Control conference

作者： Adcock, Christiane King, Ryan N. MIT Dept Mech Engn Cambridge MA 02139 USA Natl Renewable Energy Lab Golden CO 80401 USA

ISBN: (纸本)9781538654286

We demonstrate assimilation of field data from a nacelle-mounted lidar and meteorological tower into a medium fidelity Reynolds-Averaged Navier Stokes wind farm flow model to better predict the effects of atmospheric stability. Increased predictability under a variety of atmospheric conditions can lead to more effective control design and optimization of a wind farm. In particular, atmospheric stability affects wind turbine wake propagation and, therefore, aspects of wind farm control and performance, such as active wind farm control, layout optimization, and power output. Accurately modeling wakes in different stability conditions remains a persistent challenge. This paper presents an optimization framework that leverages high-fidelity field or simulation data to correct a lower-fidelity flow model. Optimal model corrections are found by solving a regularized, high-dimensional, gradient-based optimization problem using adjoint flowfield information. We validate the trained model against large eddy simulation results, and perform separate gradient-based layout optimizations of a simulated utility-scale wind farm to maximize power. Using the data driven model corrections, we find that atmospheric stability significantly impacts layout optimization and power production: the optimal layout for stable conditions produced 9.1% more power than the optimal layout for unstable conditions, and the optimal layout for neutral conditions underperformed by 8.5% in unstable conditions.

关键词： Atmospheric modeling Wind farms Data models Stability analysis Wind turbines optimization Laser radar"

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Optimal QoS-driven Power Allocation for Energy Harvesting Wireless Ad-Hoc Networks Using FBC

Optimal QoS-Driven Power Allocation for Energy Harvesting Wi...

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IEEE Global Communications conference (GLOBECOM)

作者： Zhang, Xi Wang, Jingqing Poor, H. Vincent Texas A&M Univ Dept Elect & Comp Engn Networking & Informat Syst Lab College Stn TX 77843 USA Princeton Univ Dept Elect Engn Princeton NJ 08544 USA

ISBN: (纸本)9781728109626

In the last few decades, the statistical delay-bounded quality-of-service (QoS) technique has been proposed and investigated to support delay-bounded 5G multimedia wireless services In addition, energy harvesting (EH) based systems, which enable mobile devices to harvest energy from various external sources, have been designed to address the energy scarcity problem. Researchers have recently integrated EH based systems with short-packet communications for their potential benefits of small payloads and low latency to support reliable multimedia data transmissions. Under the short delay requirements for the low-latency 5G multimedia wireless services, it is not ideal to apply the traditional Shannon capacity for modeling the data rate under the error-rate bounded in the non-asymptotic regime. Accordingly, researchers have developed the finite wireless data transmission rate in the non-asymptotic regime. However, it is challenging to determine the convexity of the effective-capacity maximization problem subject to the statistical delay-bounded and error-rate bounded QoS constraints due to the complexity of analyzing the maximization problem in the non-asymptotic regime. To overcome these challenges, we design the EH based cross-layer optimization scheme in supporting the statistical delay-bounded and error-rate bounded QoS requirements in the finite blocklength regime in the following steps. First, we characterize the EH based system models under finite blocklength coding (FBC). Second, we derive and analyze the convexity of the epsilon-effective capacity maximization problem for our proposed EH scheme in the finite blocklength regime. Finally, we conduct several simulation evaluations which validate our proposed EH scheme under the statistical delay-bounded and error-rate bounded QoS constraints in the finite blocklength regime.

关键词： Energy harvesting finite blocklength coding epsilon-effective capacity statistical delay-bounded quality of service (QoS) requirement 5G wireless ad-hoc networks

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