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IEEE 25th International conference on Intelligent Transportation Systems (ITSC)

作者： Sadid, Hashmatullah Qurashi, Moeid Antoniou, Constantinos Tech Univ Munich TUM Chair Transportat Syst Engn Munich Germany

ISBN: (数字)9781665468800

ISBN: (纸本)9781665468800

Microscopic traffic models (MTMs) are widely used for assessing the impacts of autonomous and connected autonomous vehicles (AVs/CAVs). These models use car following (CF) and lane changing models to replicate the AV and CAV driving behaviors. Several studies attempt to replicate the accurate configuration of these behaviors (especially CF behavior) with many state-of-the-art modeling methods. However, they need to define certain parameters either based on assumptions or estimation by trajectory data from the limited field experiment of AVs and CAVs, and the impacts prediction accuracy depends on the definition of these parameters. For human-driven vehicles, these parameters mimic human drivers, whereas, for AVs and CAVs, most of these parameters could be controlled by an agent (AV and CAV). Therefore, it is possible to train AVs and CAVs to behave in a way that could potentially enhance their related impacts, e.g., traffic efficiency, emissions, and safety. Thus, this paper proposes an optimization framework that tends to find sets of optimized driving parameters for AVs and CAVs under different varying scenarios to achieve pre-defined policy targets (e.g., reducing travel time, number of conflicts). The proposed framework comprises an optimization module and a simulation environment. The differential evolution (DE) method is used within the optimization module to find the optimal values of the CF parameters. The simulation environment is a SUMObased platform where several simulations are run under certain scenario conditions. An experimental setup is designed to apply the proposed framework under different scenarios of mixed traffic and demand situations. The findings of this study reveal that safety could be potentially improved by optimized values of CF model parameters. For each policy, where higher weight is allocated to safety, generated optimized parameters significantly improve safety as well as efficiency.

关键词： Autonomous vehicles microscopic modelling optimization traffic safety

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optimization Design of Contactor Driver for Electric Vehicle 2

Optimization Design of Contactor Driver for Electric Vehicle

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2nd IEEE International Power Electronics and Application Symposium, PEAS 2023

作者： Ao, Gu Qiang, Zhang Haitai, Huang Yongbin, Hong School of Electrical Engineering and Automation Xiamen University of Technology Xiamen China College of Electrical Engineering Qingdao University Qingdao China

ISBN: (纸本)9798350313765

The control system of new energy electric vehicles generally uses low-voltage batteries for power supply, including contactors that control the on-off of power lines. For this reason, contactors in cars are usually driven step up-down converters. This article compares and analyzes the driving schemes between constant-type current, stepped-type current, and curved-type current by modeling and simulating the electromagnetic mechanism of the contactor. The simulation results show that the contactor driven by the curve current has better dynamic characteristics. A prototype of contactor driver with 9~ 18V input was constructed based on the buck-boost converter. The experimental results showed that compared with the traditional constant-type current or voltage drive scheme, the curved-type current scheme reduced the number of bounces by 67%, the bounce time by 60%, and the closing time was only extended by 2ms. At the same time, the contactor holding power consumption was only 8.3% of the original, effectively optimizing the working performance of the contactor. © 2023 IEEE.

关键词： contactor driver current optimization dynamic characteristics

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Improving Photonic Crystal AND Gate Performance Via optimization Using Machine Learning 13

Improving Photonic Crystal AND Gate Performance Via Optimiza...

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13th International conference on System modeling and Advancement in Research Trends, SMART 2024

作者： Kumar, Krishan Dharuman, Narrain Prithvi Bhat, Smita Raghavendra Mane, Hrishikesh Rajesh Jain, Arpit Mali, Akash Balaji Bhagat Phool Singh Mahila Vishwavidyalaya Department of Ece Haryana Sonipat India National Institute of Technology Tamil Naidu Trichy India Independent Researcher KA 581402 India Independent Researcher Pune411014 India Koneru Lakshmaiah Education Foundation Department of Computer Science & Engineering A.P. Guntur India Midc Maharashtra Pune411019 India

ISBN: (纸本)9798350380583

A new window of space has unlocked the development of depressed-capacity, speedy ocular structures by way of current breakthroughs in a photonic crystal. Photonic crystals will authorize AND gates, which are the fundamental elements in incorporated computer circuits for mathematical plans. This research provides an order for reconstructing the effectiveness of AND gates that is to say established machine intelligence. To train on a dataset, use the Extra Trees Regressor model. Using the judgments from the imitation to forecast the power production for miscellaneous scenes for recommendation and limits. The verdicts signify that the model can create precise forecasts about the product capacity utilizing a Root Mean Square Error (RMSE) A RMSE of 0.18. The model is therefore used to find the highest in-rank principles for the mesh constant and pole range. The ideal values for R and x are driven by expected 0.05 um and 0.12 um, individually. Using the Extra Trees Regressor's prophecies for dependent computations, the research delves further into the addition process for optical port outputs. The effect of determinants like bar sweep and mesh fixed on fence functioning is intentional in detail, with accompanying importance on how these limits influence the achievement of advantageous yield states. The results of the simulation illustrate well that the amended limits can imitate the AND door behaviour in the photonic clear model © 2024 IEEE.

关键词： Mesh generation

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Voltage Waveform optimization Through Data-driven modeling in Electrohydrodynamic Jet Printing

Voltage Waveform Optimization Through Data-Driven Modeling i...

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American Control conference (ACC)

作者： Angelo Hawa Kira Barton Department of Mechanical Engineering University of Michigan Ann Arbor MI USA Department of Robotics University of Michigan Ann Arbor MI USA

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

Micro-additive manufacturing techniques pertaining to material jetting have demonstrated strong applicability in the fields of printed electronic and photonic devices. Nano-scale patterning has been achieved using electrohydrodynamic jet (e-jet) printing, which utilizes a series of high voltage pulses to precisely deposit ink in the form of printed patterns. Previous studies have successfully implemented learning control frameworks to achieve desired printing performance by adjusting the magnitude and timing of the voltage pulse. However, optimization of the input shape from a process-driven perspective has not been analyzed, and the risks of nozzle clogging and printing regime fluctuations remain as challenges in maintaining stable performance. Additionally, a knowledge gap persists in characterizing the effects of modulating the baseline voltage on temporal and volumetric dynamics of the jetting process, which serve to provide critical time constants in the design of the input shape. This work implements data-driven modeling techniques to quantify the effects of varying the pulsed and baseline voltages while developing a process-driven optimization algorithm for promoting stable jetting, furthering the foundation for implementation of control strategies for e-jet printing.

关键词： Printing Data-driven modeling Low voltage Shape simulation High-voltage techniques Timing

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An improved RNN modeling algorithm for flotation process of copper-silver ore 34

An improved RNN modeling algorithm for flotation process of ...

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34th Chinese Control and Decision conference (CCDC)

作者： Wang, Kang Pang, Liwei Li, Xiaoli Zhao, Xin Beijing Univ Technol Fac Informat Technol Beijing 100124 Peoples R China Beijing Key Lab Computat Intelligence & Intellige Beijing 100124 Peoples R China Minist Educ Engn Res Ctr Digital Community Beijing 100124 Peoples R China China Railway 19th Bur Grp Min Investment Co Beijing 100161 Peoples R China

ISBN: (纸本)9781665478960

Concentrate grade is an important evaluation index in the flotation process, which reflects the rich degree of specific recovery components in the concentrate. In this paper, the copper and silver ore grades in LinXi Mining Co., Ltd are taken as the research object. Given the difficulty in identifying the flotation process through mechanism modeling, the recurrent neural network model of the flotation process is established by using the idea of data-driven. Considering that the learning parameters are randomly selected, an improved RNN model is proposed by introducing the index function which optimizes the model parameters to obtain better modeling performance. The simulation results show that the improved recurrent neural network model can effectively identify the flotation process compared with the traditional RNN model and ARMAX model.

关键词： Flotation process Recurrent neural network Concentrate grade Data driven Model optimization

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Interface Development for Digital Twin of an Electric Motor Based on Empirical Performance Model

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IEEE ACCESS 2022年 10卷 15635-15643页

作者： Rassolkin, Anton Rjabtsikov, Viktor Kuts, Vladimir Vaimann, Toomas Kallaste, Ants Asad, Bilal Partyshev, Andriy Tallinn Univ Technol Dept Elect Power Engn & Mechatron EE-19086 Tallinn Estonia Tallinn Univ Technol Dept Mech & Ind Engn EE-19086 Tallinn Estonia Univ Limerick Elect & Comp Engn Dept Limerick V94 T9PX Ireland

The concept of Digital Twin is creating and maintaining a digital representation of the real physical entity and supporting its performance utilizing simulation and optimization tools, which are fed with the real data obtained from the physical equipment. Development and implementation of the Digital Twin technology are one of the main challenges for today's industry, more detailed studies are needed on design methods for Digital Twins. Besides using Digital Twin as a high-quality simulation, one of the commitments is monitoring and maintaining control of the whole system via a constant live link between virtual and physical entities. The related research study presents a detailed structural description of the developed Digital Twin virtual entity and the development of a framework that allows Robot Operating System (ROS) to securely communicate with remote Digital Twins via the Internet and harness ROS's adaptability across vast distances and multiple systems. This paper is an extended version of the authors' International conference on Electrical Power Drive Systems (ICEPDS20) paper, in which we propose a development case study of Digital Twin for an electric motor based on an empirical performance model.

关键词： Bridges Digital twin Solid modeling Induction motors Servers Data models Linux Motor drives model-driven development telemetry digital twin

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Learning optimization-based Control Policies Directly from Digital Twin simulations

Learning Optimization-based Control Policies Directly from D...

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IEEE conference on Control Technology and Applications (CCTA)

作者： Menner, Marcel Chakrabarty, Ankush Berntorp, Karl Di Cairano, Stefano Mitsubishi Elect Res Labs Cambridge MA 02139 USA

ISBN: (数字)9781665473385

ISBN: (纸本)9781665473385

This paper proposes to use a digital twin of a dynamical system directly for optimization-based control. It proposes an algorithm based on an Unscented Kalman Filter (UKF) to solve optimization-based control problems, where the system dynamics is encoded in the digital twin. The UKF-based algorithm uses simulations of a digital twin directly to optimize the control policy and does not require gradients to be computed-making it suitable for differential-algebraic constraints, where gradients may be inaccessible. The proposed UKF-based algorithm does not require explicit knowledge of the internal model of the digital twin, nor the control map;that is, it is a purely simulation data-driven approach. The main advantage is that a high-precision simulation-oriented digital twin can approximate the physical dynamical system more accurately than an analytical control-oriented model and thus, can improve the performance of the controller. The digital twin-based optimal control approach is evaluated on two case studies. First, a pendulum on a cart is optimized to swing up and stabilize. Second, a crane controller is optimized to avoid oscillations of the load.

关键词： Cranes System dynamics Heuristic algorithms Computational modeling Optimal control Digital twins Kalman filters

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AI-driven Multi-Objective UAV Route optimization 24

AI-Driven Multi-Objective UAV Route Optimization

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Proceedings of the Winter simulation conference

作者： Sahil Belsare Ashwin Devanga Mohammad Dehghanimohammadabadai Mechanical and Industrial Engineering Department Northeastern University Boston MA USA

ISBN: (纸本)9798331534202

Unmanned Aerial Vehicles have proven to enhance customer service and increase efficiency in supply chain management. They offer greater flexibility, ease of operation, and bypass traffic congestions by flying directly between nodes. This paper presents an innovative version of the Team Orienteering Problem with Time Windows and Charging Stations. The proposed model integrates various optimization approaches, including heuristics and AI-driven methods. The primary objectives are to maximize service rewards, minimize total travel distance, and mitigate out-of-charge incidents. Experiments are conducted to demonstrate the competency of the applied AI-enabled approach in various scenarios.

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Planar modeling and Sim-to-Real of a Tethered Multimaterial Soft Swimmer driven by Peano-HASELs

Planar Modeling and Sim-to-Real of a Tethered Multimaterial ...

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IEEE/RSJ International conference on Intelligent Robots and Systems (IROS)

作者： Gravert, Stephan-Daniel Michelis, Mike Y. Rogler, Simon Tscholl, Dario Buchner, Thomas Katzschmann, Robert K. Swiss Fed Inst Technol Dept Mech & Proc Engn Soft Robot Lab Tannenstr 3 CH-8092 Zurich Switzerland

ISBN: (数字)9781665479271

ISBN: (纸本)9781665479271

Soft robotics has the potential to revolutionize robotic locomotion, in particular, soft robotic swimmers offer a minimally invasive and adaptive solution to explore and preserve our oceans. Unfortunately, current soft robotic swimmers are vastly inferior to evolved biological swimmers, especially in terms of controllability, efficiency, maneuverability, and longevity. Additionally, the tedious iterative fabrication and empirical testing required to design soft robots has hindered their optimization. In this work, we tackle this challenge by providing an efficient and straightforward pipeline for designing and fabricating soft robotic swimmers equipped with electrostatic actuation. We streamline the process to allow for rapid additive manufacturing, and show how a differentiable simulation can be used to match a simplified model to the real deformation of a robotic swimmer. We perform several experiments with the fabricated swimmer by varying the voltage and actuation frequency of the swimmer's antagonistic muscles. We show how the voltage and frequency vary the locomotion speed of the swimmer while moving in liquid oil and observe a clear optimum in forward swimming speed. The differentiable simulation model we propose has various downstream applications, such as control and shape optimization of the swimmer;optimization results can be directly mapped back to the real robot through our sim-to-real matching.

关键词： Deformable models Shape Oils Pipelines Soft robotics Three-dimensional printing optimization

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Data-driven Solutions and Uncertainty Quantification for Multistage Stochastic optimization 24

Data-Driven Solutions and Uncertainty Quantification for Mul...

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Proceedings of the Winter simulation conference

作者： Yunhao Yan Henry Lam Dept. of Industrial Eng. and Operations Research Columbia University New York NY USA

ISBN: (纸本)9798331534202

Multistage stochastic optimization problems appear commonly in various disciplines in operations management and system control. While computational methods have been studied, they are mostly restricted to two-stage problems or otherwise require strong assumptions. In this paper, we propose a simple data-driven solution technique and uncertainty quantification method for these problems, based on natural multisample generalizations of the well-known sample average approximation and the so-called single replication procedure. Under the assumptions of stagewise independence and the use of parameterized policies, we justify statistical consistency and a coverage guarantee on bounding the optimality gap using our approaches. Our developments entail the establishment of several new statistical properties of the so-called multisample U-process that closely connect to multistage stochastic optimization.

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