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System Reliability and Safety Engineering (SRSE), International Conference on

作者： Deng Jianhui Liu Yanyan Liu Pengpeng Huang Jine PLA PLA 92942BeijingChina University of Science and Technology Beijing School of Mechanical Engineering Beijing China

ISBN: (纸本)9781665401616

In order to solve the problem of reliability deployment of complex electromechanical equipment, the functional relationships between the reliability and cost of each subsystem of complex electromechanical equipment are analyzed in this paper. Moreover, Pareto multi-objective optimization and improved artificial bee colony algorithm were used to solve the reliability optimal configuration model to improve the reliability of complex electromechanical equipment and minimize the development cost, maintenance cost and total cost of the ***, according to the Pareto optimal solution set, the PROMETHEE-II method is used to optimize the reliability deployment scheme of the optimal solution set, and the comprehensive optimal system reliability deployment scheme is obtained. The effectiveness of the proposed method was illustrated by using an equipment example, and the results shown that the total cost of the system can be obviously reducedon the premise of meeting the reliability requirements of the system.

关键词： Analytical models Costs Diesel engines Maintenance engineering Pareto optimization Reliability engineering artificial bee colony algorithm

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Reactive Power Optimization of Active Distribution Network Considering Mobile Energy Storage

Reactive Power Optimization of Active Distribution Network C...

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International Conference on Power System Technology (POWERCON)

作者： Qian Zhou Yiming Xu Jiangsu Electric Power Research Institute Nanjing China Mentor High School Mentor USA

ISBN: (纸本)9781665407380

Reactive power optimization (RPO) is an effective way to improve the power balance and reduce the risk of voltage violation in active distribution networks (ADN). However, traditional reactive power optimization methods mainly rely on stationary equipment and ignore the utilization of flexibility resources such as mobile energy storage systems (MESSs). This paper exploits the MESSs to provide localized reactive power support and proposes a day-ahead reactive power scheduling model with consideration of MESSs and conventional reactive power compensators. In the proposed model, the optimal MESS routing in the feeder can be decided and the reactive power output of the MESSs and conventional reactive power compensators can be optimally coordinated to minimize the node voltage deviations in active distribution network. By considering discrete and continuous reactive power compensators, the optimization problem can be solved effectively by the artificial bee colony (ABC) algorithm due to its strong global searching ability. The effectiveness of the proposed method is validated with the IEEE 33-node distribution test system.

关键词： Reactive power Optimization methods Voltage artificial bee colony algorithm Search problems Routing Active distribution networks

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Sensor Scheduling Based on Risk for Target Tracking

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IEEE SENSORS JOURNAL 2019年第18期19卷 8224-8232页

作者： Pang, Ce Shan, Ganlin Army Engn Univ China Zhengzhou 050000 Hebei Peoples R China

A sensor scheduling approach focusing on managing the operational risk in target tracking is proposed. The scheme selects sensor actions so that the operational risks are the minimum. First, given the definition, existence of risk in sensor scheduling is analyzed. Second, the target missing risk and the sensor radiation interception risk are summed to create the sensor scheduling objective functions, including myopic sensor scheduling and non-myopic sensor scheduling. Furthermore, to obtain sensor management schemes according to the objective functions, the improved bee colony algorithm based on double-roulette and in combination with the particle swarm optimization algorithm is proposed. Finally, simulations are carried out to illustrate the models and algorithms in the paper possess some advantages over existing ones, including being more practical, keeping nearly the same or even better tracking performance with lower risk values, and owing better sensor scheduling solutions.

关键词： Sensor scheduling target tracking interception probability target missing probability operational risk artificial bee colony algorithm

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Geometric analysis and constrained optimization of woven z-pinned composites for maximization of elastic properties

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COMPOSITE STRUCTURES 2019年 210卷 553-566页

作者： Esmaeeli, Meysam Nami, Mohammad Rahim Kazemianfar, Behzad Shiraz Univ Sch Mech Engn Shiraz Iran

In this study, an optimization problem is carried out for maximizing the out-of-plane elastic constants of woven z-pinned composites, subjected to some constraints on their in-plane elastic constants and geometric parameters. A unit-cell model is used to obtain the elastic constants as functions of geometric parameters including the pin radius and distribution density, the resin-rich zone length, the unit-cell length, the yarn thickness and width, and the yarn waviness created by z-pinning or weaving. A parametric study on the unit-cell geometry is conducted to evaluate the optimization variables and determine whether they are effective enough on the elastic properties or not. Using the key results of the parameter study, which are the equality of the yarn width and the unit-cell length as well as selecting the lowest practical yarn thickness, the constrained optimization problem is defined and solved using a modified artificial bee colony algorithm. Significant improvements in the out-of-plane constant against controlled reductions in the in-plane ones are observed. The more flexible the constraints on the in-plain constants, the better the out-of-plane constants. The optimum out-of-plane elastic modulus is greatly dependent on the pin distribution density and the ratio of the yarn width to the pin radius.

关键词： Woven z-pinned composites Elastic properties Optimization artificial bee colony algorithm

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A Comparative Study on Population-Based Evolutionary algorithms for Multiple Traveling Salesmen Problem with Visiting Constraints

A Comparative Study on Population-Based Evolutionary Algorit...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Cong Bao Qiang Yang Xu–Dong Gao Jun Zhang School of Artificial Intelligence Nanjing University of Information Science and Technology Nanjing China Zhejiang Normal University Jinhua China Hanyang University Ansan South Korea Chaoyang University of Technology Taichung County Taiwan

ISBN: (纸本)9781728190495

The multiple traveling salesmen problem with visiting constraints (VCMTSP) is an extension of the multiple traveling salesmen problem (MTSP). In this problem, some cities are restricted to be only accessed by certain salesmen, which is very common in real-world applications. In the literature, evolutionary algorithms (EAs) have been demonstrated to effectively solve MTSP. In this paper, we aim to adapt three widely used EAs in solving MTSP, namely the genetic algorithm (GA), the ant colony optimization algorithm (ACO), and the artificial bee colony algorithm (ABC), to solve VCMTSP. Then, we conduct extensive experiments to investigate the optimization performance of the three EAs in solving VCMTSP. Experimental results on various VCMTSP instances demonstrate that by means of its strong local exploitation ability, ABC shows much better performance than the other two algorithms, especially on large-scale VCMTSP. Though GA and ACO are effective to solve small-scale VCMTSP, their effectiveness degrades drastically on large-scale instances. Particularly, it is found that local exploitation is very vital for EAs to effectively solve VCMTSP. With the above observations, it is expected that this paper could afford a basic guideline for new researchers who want to take attempts in this area.

关键词： Ant colony optimization Scalability Urban areas Evolutionary computation Traveling salesman problems artificial bee colony algorithm Computational efficiency

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Power Generation Cost Minimization of An Islanded Diesel/Wind Turbine/Fuel Cell Microgrid System

Power Generation Cost Minimization of An Islanded Diesel/Win...

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International Conference on Electrical, Electronics, Communication, Computer and Optimization Techniques (ICEECCOT)

作者： Duy C. Huynh Matthew W. Dunnigan Ho Chi Minh City University of Technology (HUTECH) Ho Chi Minh City Vietnam Heriot-Watt University Edinburgh United Kingdom

ISBN: (纸本)9781665432733

Microgrid systems are becoming more and more popular and important to supply the power demand locally so that the operation and stability of the regional grid is improved. Additionally, the microgrid system is also required to operate optimally under various scenarios. This paper proposes a minimization for the power generation cost of the islanded microgrid system which is based a chaos artificial bee colony (ABC) algorithm. The microgrid system is assumed with diesel generators, wind turbine generators, and fuel cell plants. The numerical results of using the chaos ABC algorithm is compared to the ABC, particle swarm optimization (PSO), and Chaos PSO algorithms. The comparison shows the effectiveness of the proposal.

关键词： Chaos Costs Microgrids Power system stability artificial bee colony algorithm Minimization Generators

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Path Planning For Unmanned Air Vehicles Using An Improved artificial bee colony algorithm

Path Planning For Unmanned Air Vehicles Using An Improved Ar...

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第三十一届中国控制会议

作者： Lai Lei,Qu Shiru Department of Automatic Control,Northwestern Polytechnical University,Xi'an 710072

Unmanned Aerial Vehicles(UAV) path planning can be considered as a complicated function optimization problem with constraint *** based algorithm,especially the artificial bee colony(ABC) algorithm,is known as an effective tool to solve this *** algorithm is a relatively predominant optimization technique with an advantage of having fewer control parameters over other population *** the ergodicity and the stochastic of the chaotic map,we propose a modified strategy of initialization for the standard ABC,which utilizing the logistic map and opposition based learning to generate the initial population as well as the scout bee *** addition,the employed bee search equation is modified by adding weight coefficients for the purpose of increasing the convergence *** we test the modified artificial bee colony algorithm in four function optimization problems and path planning *** results demonstrate a superior performance of our algorithm in solving UAV path planning in two dimensions compare with the standard ABC algorithm.

关键词： Path planning artificial bee colony algorithm chaotic map opposition based learning

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Weight Optimization for LQG Controller Based on the artificial bee colony algorithm

Weight Optimization for LQG Controller Based on the Artifici...

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2012 Conference on Modelling, Identification and Control (MIC2012)

作者： Weidong Wang Yijuan Jing Li Yang Boyuan Ma Zhengguo Fu School of Electrical and Mechanical Engineering Xidian University

In large antenna servo control systems,Linear Quadratic Gaussian(LQG) controller is superior to the proportional integral(PI) controller in terms of stability,rapidity and wind disturbance ***,there is still no deterministic method to design the weight matrixes that affect the performance of LQG *** solve this problem,a method based on the artificial bee colony(ABC) algorithm is proposed,which aims at optimizing the close-loop system transient response *** searching and local searching are conducted in each iterative step in the ABC algorithm so that searching efficiency is greatly *** in a weight matrixes optimization problem for a large antenna servo with LQG controller,the algorithm is satisfactory in simulation result,the control effect is better than that based on the trial and error method.

关键词： artificial bee colony algorithm LQG controller Weight optimization Large antenna servo system

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Distributed consensus tracking of unknown nonlinear chaotic delayed fractional-order multi-agent systems with external disturbances based on ABC algorithm

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COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION 2019年第Jun.期71卷 101-117页

作者： Hu, Wei Wen, Guoguang Rahmani, Ahmed Yu, Yongguang Cent Lille UMR CNRS 9189 CRIStAL F-59651 Villeneuve Dascq France Beijing Jiaotong Univ Sch Sci Beijing 100044 Peoples R China

In this paper, the distributed consensus tracking of unknown nonlinear chaotic delayed fractional-order multi-agent systems (FOMASs) with external disturbances is investigated, where the fractional orders and system parameters are unknown. Firstly, in order to identify the unknown parameters of the delayed nonlinear FOMASs, an efficient artificial bee colony algorithm (ABC)-based parameters estimation approach is put forward. Secondly, based on the estimated parameters, by using fractional derivative inequality and comparison principle of linear fractional equation with delay, a discontinuous distributed control protocol is proposed to make the tracking errors converge to zero asymptotically. Thirdly, to overcome the undesirable chattering phenomenon caused by the discontinuous controller, a continuous distributed control algorithm is further designed and uniformly ultimately bounded (UUB) tracking errors can be obtained and reduced as small as desired. Finally, numerical simulations are given to test the effectiveness of the proposed parameters estimation scheme and the deigned control algorithms. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Distributed consensus tracking Delayed fractional-order multi-agent systems External disturbances artificial bee colony algorithm

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Risk-based sensor scheduling for target detection

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COMPUTERS & ELECTRICAL ENGINEERING 2019年 77卷 179-190页

作者： Pang, Ce Shan, Ganlin Army Engn Univ Dept Elect & Opt Engn Shijiazhuang 05003 Hebei Peoples R China

A risk-based sensor scheduling method is proposed and applied to target detection in this paper. This paper mainly focuses on the sensor radiation interception risk and target detection risk. Firstly, the general risk-based sensor scheduling model is established;Secondly, the target detection risk model and sensor radiation risk model are proposed respectively. It is stressed that the radiation interception model is based on Partially Observed Markov Decision Process (POMDP) due to the reason that parameters of the enemy's radiation receiver are not accessible to calculate the radiation interception risk directly;Furthermore, combined with double-roulette, the basic artificial bee colony (ABC) is improved to get sensor scheduling schemes from the objective function;Ultimately, simulations are conducted and indicate that the models and the algorithm in the paper possess some advantages over existing ones. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Sensor scheduling Target detection Operational risk artificial bee colony algorithm Radar emission

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