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检索条件"任意字段=3rd Euro-NF Conference on Network Control and Optimization"

共 1649 条记录，以下是701-710 订阅

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Research on Transformer Oil Kinematic Viscosity Detection Method Based on IWOA-RBF and Multi-frequency Ultrasonic Technology 3

Research on Transformer Oil Kinematic Viscosity Detection Me...

引用

3rd International conference on control and Robots (ICCR)

作者： Xin, Zhang Xin, Wang Jilin Elect Power Co Ltd Yanbian Power Supply Co Yanbian 133000 Jilin Peoples R China Shanghai Jiao Tong Univ Ctr Elect & Elect Technol Shanghai 200240 Peoples R China

ISBN: (纸本)9781728175621

In order to achieve rapid and accurate detection of transformer oil kinematic viscosity, a transformer oil kinematic viscosity detection model based on the improved whale algorithm (IWOA) optimized RBF neural network and multi-frequency ultrasonic detection technology is proposed. First of all, use the propagation characteristics of different frequencies of ultrasonic waves in transformer oil to measure the attenuation coefficient and other parameters of its propagation in transformer oil. Then, by improving the convergence factor and weight of the whale algorithm, the efficiency, accuracy, and global and local search capabilities of the whale algorithm are improved. Finally, IWOA is used to optimize the RBF neural network to improve the prediction accuracy, and then the IWOA-RBF training experiment samples are used to obtain the transformer oil kinematic viscosity detection model. Experimental results prove that the detection model has certain practicability.

关键词： transformer oil kinematic viscosity multi-frequency ultrasonic detection technology improved whale optimization algorithm RBF neural network

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Safely Learning Dynamical Systems from Short Trajectories 3

Safely Learning Dynamical Systems from Short Trajectories

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3rd Annual conference on Learning for Dynamics and control (L4DC)

作者： Ahmadi, Amir Ali Chaudhry, Abraar Sindhwani, Vikas Tu, Stephen Princeton Univ ORFE Princeton NJ 08544 USA Google Robot New York NY USA

A fundamental challenge in learning to control an unknown dynamical system is to reduce model uncertainty by making measurements while maintaining safety. In this work, we formulate a mathematical definition of what it means to safely learn a dynamical system by sequentially deciding where to initialize the next trajectory. In our framework, the state of the system is required to stay within a given safety region under the (possibly repeated) action of all dynamical systems that are consistent with the information gathered so far. For our first two results, we consider the setting of safely learning linear dynamics. We present a linear programming-based algorithm that either safely recovers the true dynamics from trajectories of length one, or certifies that safe learning is impossible. We also give an efficient semidefinite representation of the set of initial conditions whose resulting trajectories of length two are guaranteed to stay in the safety region. For our final result, we study the problem of safely learning a nonlinear dynamical system. We give a second-order cone programming based representation of the set of initial conditions that are guaranteed to remain in the safety region after one application of the system dynamics.

关键词： learning dynamical systems safe learning uncertainty quantification robust optimization conic programming

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Day-ahead reactive-voltage optimization for active distribution network with energy storage

Day-ahead reactive-voltage optimization for active distribut...

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Electrical Engineering and control Technologies (CEECT), conference on

作者： Guozheng Huang Hongbo Wu Zhihua Feng Yong Ding Jinghua Wang Jiangmen Power Supply Bureau Guangdong Power Grid Company Jiangmen China Shan Dong Kehui Electric Power Automation Co Ltd Zibo China

With the fast-growing of distributed generators (DGs) in the distribution network, voltage control becomes more difficult, especially for the day-ahead reactive-voltage control. Moreover, it cannot be applied in practice if too many operations need to be performed by operators. Hence, this paper formulates the problem of day-ahead reactive-voltage control for a distribution network with photovoltaic and energy storage, which combines the network reconfiguration with the reactive resources in the distribution networks. The multi-period reactive optimization model with the minimizing adjustment cost of active network loss and node voltage deviation is constructed. Compared with the traditional reactive power optimization model, this model aims to make full use of PV inverters, reactive power compensation devices, and energy storage devices to realize day-ahead voltage control. A two-stage methodology is presented to solve the proposed problem. First, the network topology with the minimal number of reconfiguration in a day with the objection of minimizing the line loss is solved. Then, for each hour, the output of reactive power, including PV inverters and static var compensators and energy storage devices for each hour is solved. The effectiveness of the proposed methodology is verified on the IEEE 33-node power system.

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Emergency Material Supply for Power Enterprises Based on Internet of Things under Short-Term Prediction of Echo State network

Emergency Material Supply for Power Enterprises Based on Int...

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Advanced Electrical and Energy Systems (AEES), International conference on

作者： Xiaowei Zhao Hui Yang Shuaibing Li Yixuan Li Longlong Yi Daqi Zhang Linxia power supply company State Grid Gansu Electric Power Company Lanzhou China School of New Energy and Power Engineering Lanzhou Jiaotong University Lanzhou China

The electric power industry is one of the major national infrastructures. Affected by the geographical environment, weather, sudden natural disasters, cost control, and other factors, and with the improvement of people's living standards and the requirements of large equipment for power supply quality, power supply enterprises put forward higher requirements on how to resist risks before accidents and rapid emergency response after accidents. The establishment of emergency material supply system for power supply enterprises based on the internet of things mode is conducive to the reform of supply side structure and the optimization of resource allocation. At the same time, it is of constructive significance for the development of intelligent and automatic emergency material package management. With the help of the analysis steps of prognostics and health management (PHM), driven by the internet of things of emergency material reserves, and starting from the four structural factors of storage, cost, risk, and technology, the data acquisition, transmission, preprocessing and short-term prediction systems of emergency material packages are established respectively, to improve the operation, maintenance, and management level of power supply enterprises.

关键词： Analytical models Costs Predictive models Emergency services Internet of Things Time factors Resource management

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Reliability Analysis Using Artificial Neural network Based Adaptive Parameter Differential Evolution Algorithm 20

Reliability Analysis Using Artificial Neural Network Based A...

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3rd International conference on Robot Systems and Applications (ICRSA)

作者： Bui, N. T. Nguyen, T. T. Nguyen, V. T. Tao, N. L. Bui, N. T. Hasegawa, H. Hanoi Univ Sci & Technol Sch Mech Engn Hanoi Vietnam Shibaura Inst Technol Dept Machinery & Control Syst Tokyo Japan

ISBN: (纸本)9781450387644

Reliability analysis is one of the methods to consider the safety and stability of an engineering system. It is very important to determine whether a system is safe or not. We need to solve the complex nonlinear and implicit the limit state functions to obtain the reliability index. Traditional reliability analysis methods, First-Order Reliability Method (FORM), Second-Order Reliability Method (SORM), and Monte Carlo simulation (MCS), are not effective and have many limitations. In this paper, at the first step, an artificial neural network was used to model the limit state function. After that, the elite opposition-based learning differential evolution algorithm was selected to solve nonlinear equality constrained optimization problem to find the reliability index and the failure probability of problems in terms of random variables. The proposed method and some reference methods were applied to analyze the test problems in the literature to compare their effectiveness.

关键词： Reliability analysis neural network differential evolution optimization algorithm global search

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Path optimization for multiple humanoid robot using TLBO based AnfIS controller in obscure environment 3

Path optimization for multiple humanoid robot using TLBO bas...

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3rd International conference on Advances in Mechanical Engineering and Nanotechnology, ICAMEN 2021

作者： Kumar Kashyap, Abhishek Pandey, Anish Parhi, Dayal R. Sharma, Abhishek Mechanical Engineering Department National Institute of Technology Odisha Rourkela769008 India School of Mechanical Engineering Kalinga Institute of Industrial Technology Odisha Bhubaneswar751024 India Department of Mechanical Engineering Manipal University Jaipur Rajasthan Jaipur303007 India

Humanoid robot NAO is an intelligent reprogrammable agent designed to execute desired work using wireless control system by sensing the working environment at the same time. This article concentrates on the analysis of hybrid intelligent navigation approaches for single and multiple humanoid NAOs. It describes the optimization of a collision-free path in a static and dynamic terrain. The hybridization introduced is designed in two steps. AnfIS (Adaptive network-based Fuzzy Inference System) controller produces a transitional driving angle (TDA) using a robot location with respect to obstacle distance in all directions. It is fed to Teacher Learner based optimization (TLBO) approach that produces optimum driving angle (ODA) for the humanoid robot to guide along with its predefined target. It optimizes the path selection by taking Euclidean distance and ODA as the key factor. The hybridized controller is examined in an environment that consists of single and multiple NAOs. Case of inter-collision may occur in the path planning of multiple humanoid NAOs. It is eliminated with the integration of the dining philosopher controller in the base algorithm to prioritized one robot towards the assigned target. Simulation results demonstrate the proposed controller's efficacy and explain that it gives optimized path length and travel time. In addition, a comparative study with previously applied effective algorithms is done. © 2021 Elsevier Ltd.

关键词： controllers

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3rd International conference on Applied Science and Technology, iCAST 2020

3rd International Conference on Applied Science and Technolo...

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3rd International conference on Applied Science and Technology, iCAST 2020

ISBN: (纸本)9781728195674

The proceedings contain 38 papers. The topics discussed include: effect of turbine inclination to the performance of micro hydro power generator screw Archimedes;estimating village development index based on satellite imagery using machine learning application;optimization of capacitor placement in radial distribution system using integer encoding genetic algorithm;implementation of neural network for the liver disease classification;developing monitoring system based internet of things for vibration analysis;automatic hull fracture detection system using template matching;3D asset for web-based virtual engineering platform as implementation of industry 4.0;autonomous car based on teaching-and-playback control;and warning system design to detect suspicious activities in a network.

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control of Cricket System Using LQR controller Optimized by Particle Swarm optimization 3

Control of Cricket System Using LQR Controller Optimized by ...

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3rd International conference on Applied Mathematics, Modeling and Simulation (AMMS)

作者： Zhang, Yongli Li, Yunfei Liu, Yu Yi, Guorong Beijing Inst Technol Zhuhai Sch Informat Zhuhai Peoples R China Tianjin Univ Technol & Educ Sch Automat & Elect Engn Tianjin Peoples R China

The cricket system, as a strongly coupled, nonlinear and multivariable two dimensional cue system, is a typical representative of unstable and underactuated system. In this paper, the system is analyzed by modeling based on the cricket experimental platform, and while designing the LQR controller, the particle swarm algorithm is introduced to optimize the controller parameters to determine the optimal weight matrix Q in order to solve the difficult problem of controller parameter rectification. The simulation results show that the PSO-LQR can restore the balance of the system in a shorter period of time with enhanced stability compared to a single LQR controller, which exhibits good control performance.

关键词： controllers

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Design and development of management and control system for intelligent die forging production line 3

Design and development of management and control system for ...

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3rd World conference on Mechanical Engineering and Intelligent Manufacturing (WCMEIM)

作者： Ji, YuanLong Sun, ShuWen Liu, ZhiFeng Liu, Chenfei Beijing Univ Technol Inst Adv Mfg & Intelligent Technol Beijing Peoples R China Beijing Univ Technol Inst Adv Mfg & Intelligent Technol Beijing Peoples R China

ISBN: (纸本)9781665441094

Nowadays the forging industry has issues such as serious pollution emissions, low levels of intelligence and automation of enterprises and the complexity and diversity of underlying equipment lead to the weak information interaction between equipment. In order to solve the above problems, the forging production line management system is designed and developed in this paper, the four main function modules of system management, energy management, basic information management, and production scheduling are included in this system. The data transmission network is constructed through PROFIBUS and PROFIINET fieldbus technology to connect various devices in the process. The management system realizes basic information management, energy consumption statistical analysis, scheduling optimization and other functions in the forging production process.

关键词： Intelligent manufacturing Die forging production line Data acquisition control system

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Design and Implementation of a Dual-IP Core UAV Flight control System Based on Qsys 3

Design and Implementation of a Dual-IP Core UAV Flight Contr...

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3rd International conference on Mechatronics and Intelligent Robotics (ICMIR)

作者： Zhang, Kun Bi, Fang Hong Li, Ke Li Liang, Ying Yang, Jun Yunnan Univ Sch Informat Sci & Engn Kunming 650091 Yunnan Peoples R China

The principle and key technology of each module of flight control system of advanced UAV at home and abroad are analyzed and studied. Using Verilog HDL language optimization design completed sensor driver module, navigation control module, the flight control module and Avalon bus control module, such as using Altera corporation's latest SOPC design integrated tools Qsys constructs the IP core of navigation and control, and flight control IP core, the final design implements a dual-IP core navigation and control as the core of the UAV flight control system. Dual-IP core based on Qsys tool development of UAV flight control system not only instruction processing speed and occupy less hardware resources, and has high system integration, low cost, good robustness, refactoring is strong wait for an advantage, its performance is superior to the traditional micro controller and the DSP chip ordinary construction of UAV flight control system, has a certain application value and practical significance. (C) 2020 The Authors. Published by Elsevier B.V.

关键词： Qsys SOPC Dual-Core IP Core UAV flight control system

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