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International Conference on Power System Technology (PowerCon)

作者： Cai Changchun Wu Min Deng Lihua Deng Zhixiang Zhang Jianyong Hohai Univ Changzhou Jiangsu Peoples R China Hohai Univ Coll IOT Engn Changzhou Jiangsu Peoples R China Hohai Univ Dept Mathes & Phys Engn Changzhou Jiangsu Peoples R China

ISBN: (纸本)9781479950324

A simplified equivalent model of microgrid, based on the RBF Artificial Neural Network, is present in this paper. The proposed model is suitable for the dynamic studies of microgrids. Nonlinear mapping of RBF neural network describes the dynamic characteristics of the Point of Common Couple(PCC) of micro-grid under the connected mode. The development model is evaluated using the voltage, current and power of the PCC as the input and output of the RBF neural network in the train process. The PSO algorithm is used for the parameter optimization of RBF and improved the generalization of the dynamic model. The simulation results show the proposed modeling method in this paper is suitable and effective, and the RBF neural network based dynamic model can describe the dynamic characteristics of micro-grid accurately.

关键词： RBF neural network Equivalent Modeling particle swarm optimization algorithm Micro-grid

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Active disturbance rejection control for output force creep characteristics of ionic polymer metal composites

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SMART MATERIALS AND STRUCTURES 2014年第7期23卷

作者： Xiong, Yan Chen, Yang Sun, Zhiyong Hao, Lina Dong, Jie Northeastern Univ Sch Mech Engn & Automat Shenyang Liaoning Peoples R China

Ionic polymer metal composites (IPMCs) are a type of electroactive polymer (EAP) that can be used as both sensors and actuators. An IPMC has enormous potential application in the field of biomimetic robotics, medical devices, and so on. However, an IPMC actuator has a great number of disadvantages, such as creep and time-variation, making it vulnerable to external disturbances. In addition, the complex actuation mechanism makes it difficult to model and the demand of the control algorithm is laborious to implement. In this paper, we obtain a creep model of the IPMC by means of model identification based on the method of creep operator linear superposition. Although the mathematical model is not approximate to the IPMC accurate model, it is accurate enough to be used in MATLAB to prove the control algorithm. A controller based on the active disturbance rejection control (ADRC) method is designed to solve the drawbacks previously given. Because the ADRC controller is separate from the mathematical model of the controlled plant, the control algorithm has the ability to complete disturbance estimation and compensation. Some factors, such as all external disturbances, uncertainty factors, the inaccuracy of the identification model and different kinds of IPMCs, have little effect on controlling the output block force of the IPMC. Furthermore, we use the particle swarm optimization algorithm to adjust ADRC parameters so that the IPMC actuator can approach the desired block force with unknown external disturbances. Simulations and experimental examples validate the effectiveness of the ADRC controller.

关键词： IPMC force creep model active disturbance rejection control particle swarm optimization algorithm

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Reactive power optimization based on improved particle swarm optimization algorithm with boundary restriction

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3rd International Conference on Electric Utility Deregulation, Restructuring and Power Technologies

作者： Liu, Hong Ge, Shaoyun Tianjin Univ Sch Elect Automat Engn Tianjin 300072 Peoples R China

ISBN: (纸本)9787564112493

At present, the particle swarm optimization algorithm is not effective in dealing with discrete variables, avoiding local optimization, and satisfying all inequality constraints of voltage and power factor. Therefore, this paper employs variable reflection and integralization to find the discrete correspondent of continuous variable in the particle;and introduces chaos strategy to the searching process to strengthen the capability of finding global optimization solution. Then this paper improves the optimization solution by adjusting the voltage and power factor that exceed limits with "nine palaces" strategy, to ensure the particles in feasible solution space. At last, this paper tests the proposed algorithm with the standard IEEE sample system and some actual network planning. The comparison of calculation results with those in other literatures proves that the new algorithm has more advantages at searching speed and quality.

关键词： electric power system reactive power control voltage regulation particle swarm optimization algorithm

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Study on the application of particle swarm optimization algorithm to power regulation of CPS in interconnect power grids

Study on the application of particle swarm optimization algo...

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IEEE Electrical Power and Energy Conference

作者： Liu Bin Wang Keying Zou Qing South China Univ Technol Coll Elect Power Guangzhou 510641 Peoples R China Guangdong Med Coll Sch Pub Hlth Dept Biomed Engn Guangzhou 523808 Peoples R China

ISBN: (纸本)9781424428946

The proportion of different AGC unit under the shortfall of power in the grid is investigated. The paper adopt PSO algorithm to optimize units of AGC (automatic generation control) which regulate the distribution of power and be in CPS controlling strategy. The optimal solution is hard to obtain by using average distribution but can be worked by using standard PSO algorithm, and then the CPS level can achieve the optimal under economic conditions. The paper proved the effectiveness of the algorithm by computing example simulation.

关键词： particle swarm optimization algorithm control performance standard automatic generation control regulation power

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Cellular particle swarm optimization algorithm for Logistics Distribution Locating Problem

Cellular Particle Swarm Optimization Algorithm for Logistics...

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International Seminar on Future BioMedical Information Engineering

作者： Liu, Yi Hangzhou Dianzi Univ Inst Management Sci & Informat Engn Hangzhou 310018 Zhejiang Peoples R China

ISBN: (纸本)9780769535616

Logistics distribution locating problem is an important area in Logistics, which select the most reasonable location of distribution centers from many places. This paper establish the Cellular PSO algorithm, which combine the particle swarm optimization algorithm and cellular automata. This algorithm was tested in the simulation experiment, and the result indicate that the Cellular PSO algorithm is a effective method of solving the problem of choosing the distribution centers location which can overcome the low precision of the basic particle swarm optimization algorithm. In additional, the Cellular PSO algorithm has high quality and efficiency of searching.

关键词： Cellular Automata particle swarm optimization algorithm Logistics Distribution Centers Location

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Bandwidth and Power Allocation for Two-Way Relaying in Overlay Cognitive Radio Systems

Bandwidth and Power Allocation for Two-Way Relaying in Overl...

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IEEE Global Communications Conference

作者： Ahmad Alsharoa Hakim Ghazzai Elias Yaacoub Mohamed-Slim Alouini King Abdullah University of Science and Technology (KAUST) Qatar Mobility Innovations Center (QMIC). Qatar Science and Technology Park

ISBN: (纸本)9781479935130

In this paper, the problem of both bandwidth and power allocation for two-way multiple relay systems in overlay cognitive radio (CR) set-up is investigated. In the CR overlay mode, primary users (PUs) cooperate with cognitive users (CUs) for mutual benefits. In our framework, we propose that the CUs are allowed to allocate a part of the PUs spectrum to perform their cognitive transmission. In return, acting as an amplify-and-forward two-way relays, they are used to support PUs to achieve their target data rates over the remaining bandwidth. More specifically, CUs acts as relays for the PUs and gain some spectrum as long as they respect a specific power budget and primary quality-of-service constraints. In this context, we first derive closed-form expressions for optimal transmit power allocated to PUs and CUs in order to maximize the cognitive objective. Then, we employ a strong optimization tool based on particle swarm optimization algorithm to find the optimal relay amplification gains and optimal cognitive released bandwidths as well. Our numerical results illustrate the performance of our proposed algorithm for different utility metrics and analyze the impact of some system parameters on the achieved performance.

关键词： Overlay cognitive radio systems Two-way relaying technique particle swarm optimization algorithm

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Fuzzy Comprehensive Evaluation for Transmission Grid Planning Based on Combination Weight

Fuzzy Comprehensive Evaluation for Transmission Grid Plannin...

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2014 International Conference on Power and Energy(ICPE 2014)

作者： Z.H.LI Y Lin W.H.Chen D.H.You G.Wang M.L.Dong Q.R.Chen Y.Zou J.Hu Guangdong Power Grid Development Research Institute Co. Ltd State Key Laboratory of Advanced Electromagnetic Engineering and Technology of Huazhong University of Science and Technology

In order to remedy the defect that the determination of weight in fuzzy comprehensive evaluation is impacted by subjectivity, the combination weight is introduced. In this paper, the optimization Model combines the subjective weight and objective weight, which is solved by PSO, is built. At the same time, In order to give full consideration to the uncertain and fuzzy factors which involved in the grid planning, this paper combines the combination weight and fuzzy comprehensive evaluation to assess the grid-planning scheme. The calculation results of IEEE Garver-6 show that the proposed fuzzy comprehensive evaluation system is clear in theory and convenient to calculate, the combination weight is objective and reasonable as well as its results are scientific and intuitive.

关键词： grid planning scheme fuzzy comprehensive evaluation combination weight particle swarm optimization algorithm

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A New Two-stages PSO algorithm for Railway Trajectory Planning on GIS System

A New Two-stages PSO Algorithm for Railway Trajectory Planni...

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IEEE International Conference on Intelligent Transportation Systems

作者： Jun Liu Tianyun Shi Inst. of Comput. Technol. Beijing China

ISBN: (纸本)9781479960798

Smart railway trajectory planning is one of the most interesting and important topics in the fields of intelligent railway transportation, computer science and evolutionary computation, etc. Several objectives and constraints of railway trajectory planning problem are closely related to the distance factor, the construction cost, the altitude factor and the comfortability, etc. More importantly, the new particle swarm optimization (PSO) algorithm, including two optimization sub-stages, firstly optimize the coordinate in y-axis and secondly optimize the latitude in z-axis to design the optimal 3-D railway trajectory. Numerical results highlight that the new two-stages PSO algorithm can provide one realistic optimal trajectory from any two cities in the complicated three-dimensional GIS scenario, such as Chang Sha city and Nan Chang city.

关键词： evolutionary computation geographic information systems particle swarm optimisation railway engineering Chang Sha city GIS system Nan Chang city altitude factor computer science construction cost distance factor intelligent railway transportation optimal 3D railway trajectory optimal trajectory particle swarm optimization algorithm railway trajectory planning problem smart railway trajectory planning three-dimensional GIS scenario two-stages PSO algorithm algorithm design and analysis Cities and towns Linear programming Planning Rail transportation Trajectory evolutionary algorithm Rail transportation algorithm design and analysis Railway engineering Cities and towns geographic information systems Construction costs particle swarm optimization trajectory Distance factor computer science linear programming trajectory planning railways

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Path planning for unmanned vehicle searching based on sensor deployment and travelling salesman problem

Path planning for unmanned vehicle searching based on sensor...

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2014中国制导、导航与控制学术会议

作者： Bin Di Rui Zhou Yu Zhang Jun Che Science and Technology on Aircraft Control Laboratory Beihang UniversityBeijing100191 China AVIC Automatic Flight Control Research InstituteXi''an 710065 China

ISBN: (纸本)9781479946983

The path planning problem for unmanned vehicle searching over the region of interest with obstacles is investigated in this *** path planning problem is decomposed into the sensor deployment problem and the travelling salesman problem based on the fundamental finding that the vehicle could search the region that covered by the sensor if the vehicle pass through the position where the sensor is *** positions of the sensors deployed to cover the region completely are obtained by solving the sensor deployment *** the positions of the deployed sensors as the waypoints that the vehicle has to travel through,the shortest path connecting all the waypoints can be obtained by solving the travelling salesman *** cooperatively coevolving particle swarm optimization algorithm with multiple update rules is newly developed for the sensor deployment *** simulation results demonstrate the feasibility of the proposed methods.

关键词： mobile robots particle swarm optimisation path planning remotely operated vehicles sensor placement travelling salesman problems particle swarm optimization algorithm sensor deployment travelling salesman problem unmanned vehicle optimization particle swarm optimization Path planning Robot sensing systems Search problems Vehicles

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Integrated Design of Missile Guidance and Control:Active Disturbance Rejection Control Method

Integrated Design of Missile Guidance and Control:Active Dis...

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2014中国制导、导航与控制学术会议

作者： Maopeng Ran Yifen Chen Qing Wang Chaoyang Dong Aojia Ma School of Automation Science and Electrical Engineering Beihang UniversityBeijing100191 China The 8th Institute of Shanghai Academy of Spaceflight TechnologyShanghai201109 China School of Aeronautic Science and EngineeringBeihang UniversityBeijing100191 China

ISBN: (纸本)9781479946983

In this paper,we present an active disturbance rejection control (ADRC) based integrated guidance and control (IGC) *** IGC law is designed using the backstepping technique,and the particle swarm optimization (PSO) algorithm is utilized to find the optimal selection of the controller *** results show that,with the application of the proposed IGC law,small miss distance can be achieved,and the system is robust against target maneuver and system uncertainties.

关键词： active disturbance rejection control control nonlinearities missile guidance particle swarm optimisation uncertain systems ADRC IGC law design PSO algorithm active disturbance rejection control method backstepping technique controller parameter selection integrated design integrated guidance and control missile control particle swarm optimization algorithm system uncertainties Aerodynamics Backstepping Educational institutions History Missiles Observers Uncertainty guided missile guidance Robust control overall design system uncertainties missile control Control nonlinearities missiles particle swarm optimization Backstepping Educational institutions uncertain systems Aerodynamics Observers

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