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3rd International Conference on Data Science and Business Analytics (ICDSBA)

作者： Li, Yuhang Nari Technol State Grid Elect Power Res Inst Co L Nari Tech Power Distribut & Rural Electrificat Br Nanjing Peoples R China

ISBN: (纸本)9781728146447

Distributed Generation plays an important role in promoting sustainable economic and social development. It has a huge contribution to optimizing energy structure, coping with climate change and protecting ecological environment. The way for selecting and fixing the capacity, therefor, is a very important part of the implementation process. Based on chaotic search and particle swarm optimization, this paper implements an economical and practical method for distributed power supply location and capacity by analyzing grid loss. Through the analysis of the example, the new algorithm, which is superior to the original particle swarm optimization algorithm in calculation accuracy, convergence velocity and optimization ability, provides a theoretical base for multi-objective planning of distributed generation supply.

关键词： component: distributed generation pso algorithm chaos search location and capacity

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RBF Neural Network Based Fast Converging Terminal Global Sliding Mode Control of Aero-engine 9

RBF Neural Network Based Fast Converging Terminal Global Sli...

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9th International Conference on Information Science and Technology (ICIST)

作者： Zhang, Yu Xie, Shousheng Ren, Litong Wang, Lei Air Force Engn Univ PLA Aviat Engn Coll Xian Peoples R China

ISBN: (纸本)9781728121062

This paper focuses on the sliding mode control of aero-engine control system with system uncertainties and disturbances. A terminal sliding mode controller with variable exponential parameter has been proposed together with a global sliding surface. It has the advantages of both terminal global sliding control and global sliding mode control scheme, that is, both finite-time high speed convergence and global robustness can be realized. The exponential parameter, which decides the contradictory relation between convergence speed and chattering amplitude, has been optimized by adaptive pso algorithm. Then to obtain the full-envelop controller, RBF neural network has been used to obtain the nonlinear mapping relation between different working conditions and the variable exponential parameter. Simulation results indicate that the proposed controller has great dynamic performance and can effectively suppress chattering.

关键词： Aero-engine terminal sliding mode global sliding surface pso algorithm RBF neural network

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Comparative study of Controller Optimisation for CSTR using Particle Swarm Optimization Technique 5

Comparative study of Controller Optimisation for CSTR using ...

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5th International Conference on Electrical Energy Systems (ICEES)

作者： Durgadevi, S. Sundari, K. Thirupura Raaghavi, D. Akshaya, R. S. Sri Sairam Engn Coll Dept Elect & Instrumentat Engn Chennai 600044 Tamil Nadu India

ISBN: (纸本)9781538692486

The Continuous Stirred Tank Reactor (CSTR) plays a main role in all chemical process industries for *** found in wide applications where the industries allow liquid, gas and solid reactions, with continuous agitation and series configuration for concentration and temperature. Hence to attain specific concentration, the full strength of solution is mixed with desired proportions of water. This is usually carried out with the help of conventional PI &PID controllers. The main objective of the proposed work is to compare and analyze the conventional controllers used in CSTR with a soft computing technique tuned PI&PID controllers for various error criteria. The conventional controllers have difficulty in dealing with problems that appear in complex non-linear processes. In order to tackle this problem and improve the dynamic response of CSTR, the reactor performance is analyzed with soft computing technique known as Particle swarm Optimization (pso).The control objective to maintain the CSTR at steady state operating point in terms of less settling time and reduced % overshoot.

关键词： CSTR conventional PI & PID controller pso algorithm error criteria

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The Optimized Scheme for FPGA-based LDPC codes using Particle Swarm Optimization 10

The Optimized Scheme for FPGA-based LDPC codes using Particl...

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10th International Conference on Information and Communication Technology Convergence (ICTC) - ICT Convergence Leading the Autonomous Future

作者： Noh, Dong-Hee Jeong, Sung-Hwan Choi, JuHwan KETI Software Convergence Cluster Jeonju South Korea

ISBN: (纸本)9781728108933

This paper proposes the enhanced BP decoding scheme of Low-density parity-check (LDPC) codes scheme using Particle Swarm Optimization (pso) algorithm. New approaches to this paper describe the BP decoding scheme using pso algorithm. Its scheme can optimize the degree distribution pairs of check and variable node over rician channel. Therefore, proposed scheme can improve the throughput performance for wireless sensor networks over the industrial environment such as military or agriculture application.

关键词： LDPC BP Decoding Decoding Complexity pso algorithm Wireless Sensor Network

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Distributed Simulation Environment of Unmanned Aerial Systems for a Search Problem 5th

Distributed Simulation Environment of Unmanned Aerial System...

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5th International Workshop on Modelling and Simulation for Autonomous Systems (MESAS)

作者： Skrzypecki, Stanislaw Pierzchala, Dariusz Tarapata, Zbigniew Mil Univ Technol Cybernet Fac Warsaw Poland

ISBN: (纸本)9783030149840;9783030149833

In the paper the programmable simulation environment for Unmanned Aerial Systems (UAS) and the preliminary research of UAV's swarm applied for a search problem in a large-scale terrain are presented. Proposed approach is based on distributed simulation, multiagent systems and multiresolution modelling in order to perform studies on UAV modelled as a swarm with determined, autonomous, combined behaviours. Some software agents have been simulated in constructive component while others have been controlled by virtual simulator (VBS3) with interoperability provided by DIS or HLA protocols. Furthermore, the biological inspired algorithms (e.g. pso algorithm and other modifications) have been used to model UAVs' actions. The preliminary results lead to conclusion of usability of the environment in solving search problem and modelling UAV's movements and behaviours.

关键词： UAS UAV's swarm Distributed simulation Autonomous systems Biological inspired algorithms pso algorithm

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A Planning Method of Charging Network for Initial Stage of Electric Vehicle Development 2019

A Planning Method of Charging Network for Initial Stage of E...

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Proceedings of the 2nd International Conference on Information Technologies and Electrical Engineering

作者： Lefeng Shi Yi Long Tingting Xu Xiaorui Hu Hang Zhan Hanlin Xia Center for Intelligent Energy Management and Applications School of Economics and Management Chongqing Normal University Chongqing China State Grid Chongqing Electric Power Research Institute State Grid Chongqing Electric Power Company Chongqing China

ISBN: (纸本)9781450372930

Coordination development between electric vehicles (EVs) and charging infrastructures is the key of propelling the diffusion of electric vehicles, especially at the initial stage. This paper taking into account both the convenience of charging of EV owners and investment cost of charging network, proposes a particle swarm optimization(pso) algorithm for planning the charging network of EVs, aiming to solve out the "chicken-egg" problem, a dilemma existing the initial period of EVs development, in which charging infrastructure investors lack investment enthusiasm, but meanwhile to trigger the purchase motivation of latent EVs users highly depends on charging convenience. The proposed method could not only support the EV charging network layout accounting for the cost of the investors but also consider the charging convenience of EVs owners. In addition, the simulation outcome also proves that our algorithm could quickly seek out the best layout scheme of charging infrastructures.

关键词： Charging network Electric vehicle pso algorithm Charging station

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Improved State Space Model Using Iterative pso for Unsteady Aerodynamic System at High AOA

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INTERNATIONAL JOURNAL OF COGNITIVE INFORMATICS AND NATURAL INTELLIGENCE 2018年第3期12卷 1-17页

作者： Luo, Guiming Zhao, Boxu Jiang, Mengqi Tsinghua Univ Sch Software Beijing Peoples R China

Due to the complex hysteresis phenomenon at a high angle of attack (AOA), modeling of unsteady aerodynamic coefficients usually encounters the problem that the parameter vector is too long and the simulation accuracy is not high. The article proposes an improved state-space model based on aerodynamics, applying Fourier analysis and the principal component analysis for model optimization. The likelihood criterion and GOIpso (Iterative Particle Swarm Optimization Based on Genetic Operator) algorithm are established under the Gaussian assumption. The iterative pso, into which the genetic algorithm's operators are integrated to calculate the optimization of the likelihood function, greatly reduced the probability of local optimization. Experiments show that the algorithm and model proposed in this paper greatly improves the model-fitting accuracy.

关键词： High Angle of Attack pso algorithm State Space Model Unsteady Aerodynamic System

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A PIλ controller for a 3rd-order Sigma-Delta Modulator

A PIλ controller for a 3rd-order Sigma-Delta Modulator

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第三十九届中国控制会议

作者： Chi Xu Yu Jin Duli Yu School of Information Science and Technology Beijing University of Chemical Technology Advanced Innovation Center for Soft Matter Beijing University of Chemical Technology

A 3-order Sigma-Delta modulator with a PI controller is proposed in this paper to improve the signal to noise ratio(SNR) and system stability. Traditional Sigma-Delta modulator mainly focused on forming an integer high order integrator to improve the SNR, whereas this paper presents a fractional-order controller instead to obtain higher SNR and better stability. Specifically, a 1-order digital integrator and a fractional-order PI controller are inserted between the AFE and the quantizer. The 1-order digital integrator can increase overall loop order to produce much higher SNR for Sigma-Delta modulator and the fractional-order PI controller allows fine tuning accuracy in seeking the coefficients for Sigma-Delta modulator and provides stability in the placement of poles and zeros for compensating the phase delays caused by system integrator parts. The parameters of PI controller are optimized by using swarm intelligent optimization algorithm. The performance and stability of the proposed 3-order Sigma-Delta modulator with PI controller are analyzed and demonstrated, respectively.

关键词： Fractional-order System Sigma-Delta Modulator digital Integrator pso algorithm

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Research on Task Scheduling in Distributed Vulnerability Scanning System

Research on Task Scheduling in Distributed Vulnerability Sca...

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作者： Jie Jiang Sixin Tang College of Computer Science and Technology Hengyang Normal University Hunan Provincial Key Laboratory of Intelligent Information Processing and Application

Network threats caused by system vulnerabilities is increasing gradually, the distributed vulnerability scanning system can scan large-scale and complex networks and report the vulnerability information. Task scheduling is one of the core components in a distributed system. In this paper, we use dynamic optimization algorithms to improve the task scheduling efficiency of distributed vulnerability scanning system, we propose a pso-based task scheduling scheme and improves the search ability of particles by adjusting algorithm parameters. We compared the time consume when using existing‘Resource Aware Scheduling algorithm'(RASA) with the basic particle swarm optimization(pso) algorithm and the improved particle swarm optimization(Ipso) algorithm. Our results show that Ipso has better performance than other scheduling methods.

关键词： Vulnerability scanning Distributed Task scheduling pso algorithm

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Lifting Wavelet De-noising Method with Dual-Threshold Based on pso algorithm

Lifting Wavelet De-noising Method with Dual-Threshold Based ...

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32nd Chinese Control Conference (CCC)

作者： Liu Sheng Zhang Qing-chun Gu Ming-ming Harbin Engn Univ Sch Automat Harbin 150001 Peoples R China

ISBN: (纸本)9781479900305

To remove the noise of signal and improve the signal-to-noise ratio, we present a lifting wavelet de-noising method With flexible dual-threshold based on pso algorithm. We use the lifting wavelet instead of traditional wavelet to decompose the in order to improve the operation speed. We use the quantization function by flexible dual-threshold to quantify the detail coefficients. By doing this, We preferably retained the fine features of the signal, while preventing the signal oscillation. pso algorithm is used to optimize the dual-threshold, in order to get the optimal threshold value, to improve the signal-to-noise ratio. The simulation and experimental results show that this new de-noising method can effectively suppress the noise, and get a higher signal-to-noise ratio and faster processing speed compared to the traditional denoising method.

关键词： Signal De-noising Lifting Vavelet Transform Flexible Dual-Threshold pso algorithm

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