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International Conference on Fluid Power and Mechatronics (FPM)

作者： Chengyu Yao Xueyun Tan Dongning Chen Shijun Lv Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China Key Lab of Heavy Machinery Fluid Power Transmission and Control of Hebei Province Yanshan University Qinhuangdao China

ISBN: (纸本)9781479987719

In view of the particle swarm optimization (PSO) algorithm's shortages of easily trapping into local optimum and premature convergence, an improvement research from the perspective of interaction mechanism among particles is made in this paper. Consider advantages and disadvantages of the current improved PSO algorithms from the aspect of force, the two-stage force particle swarm optimization (TFPSO) algorithm is proposed. The proposed algorithm, which employs staged search strategy to achieve a trade-off between global exploration and local exploitation abilities, divides search process into two stages and constructs corresponding force rules combining with the idea of attractive and repulsive forces in artificial physics. In order to demonstrate the performance of the proposed algorithm in solving optimization problems, TFPSO algorithm is compared with some well-known PSO algorithms in reliability optimization for hydraulic system. Comparison results show that TFPSO algorithm obtains the best optimization results and enhances the performance of PSO in terms of accuracy of the optimal solution and local search ability.

关键词： Force Reliability Optimization Particle swarm optimization Hydraulic systems Convergence Fault trees

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Parameters adaption of Lebesgue sampling-based diagnosis and prognosis for Li-ion batteries

Parameters adaption of Lebesgue sampling-based diagnosis and...

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2015 Annual Conference of the Prognostics and Health Management Society, PHM 2015

作者： Yan, Wuzhao Dou, Wanchun Liu, Datong Peng, Yu Zhang, Bin Department of Electrical Engineering University of South Carolina ColumbiaSC29208 United States Department of Computer Science and Technology State Key Lab. for Novel Software Technology Nanjing University NanjingJiangsu210093 China Department of Automatic Test and Control Harbin Institute of Technology HarbinHeilongjiang150080 China

ISBN: (纸本)9781936263202

Traditional fault diagnosis and prognosis (FDP) approaches are based on Riemann sampling (RS), in which samples are taken and algorithms are executed in a periodic time interval. With the increase of system complexity, the real-time implementation of this Riemann sampling-based FDP (RS-FDP) becomes a bottleneck, especially for distributed applications. To overcome this problem, a Lebesgue sampling-based FDP (LS-FDP) is proposed. LS-FDP takes samples on the fault dimension axis and provides a need-based diagnostic philosophy in which the algorithm is executed only when necessary. In previous Lebesgue sampling-based FDP, the Lebesgue length is a constant. To accommodate the change of fault dynamics, it is desirable to execute FDP algorithm more frequently when the fault growth is fast while less frequently when fault growth is slow. This requires to change the Lebesgue length adaptively. The goal of this paper is to deliver an improved LS-FDP method with varying Lebesgue length, which enables the FDP to be executed according to needs. The design and implementation of varying Lebesgue length LS-FDP based on a particle filtering algorithm are illustrated with experimental results on Li-ion batteries to verify the performances of the proposed approach. The experimental results show that the new varying LS-FDP is accurate and time-efficient on long term prognosis and also keeps a closer monitoring on the fast increase of fault size. © 2015, Prognostics and Health Management Society. All rights reserved.

关键词： Real time control

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Fuzzy dynamic output-feedback control for markov jump fuzzy bilinear system

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ICIC Express Letters, Part B: Applications 2015年第10期6卷 2883-2890页

作者： Chang, Ru Fang, Yiming Liu, Le Key Lab of Industrial Computer Control Engineering of Hebei Province College of Electric Engineering Yanshan University China National Engineering Research Center for Equipment and Technology of Cold Strip Rolling No. 438 Hebei Ave QinhuangdaoP.R China

Fuzzy dynamic output-feedback control problem is investigated for a class of fuzzy bilinear systems with Markovian jumping parameters. The transition probability matrix is assumed to be partly unknown. Based on Takagi-Sugeno (T-S) fuzzy bilinear model, a nonlinear dynamic output-feedback controller is first constructed, and in terms of linear matrix inequalities techniques, the sufficient conditions on the stochastic stability of the closed-loop fuzzy bilinear jump system are presented and proved. Finally, a numerical example is provided to illustrate the effectiveness of the proposed method. ©, 2015 ICIC Express Letters *** Rights Reserved.

关键词： Fuzzy control

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Finite-time neural network adaptive control of under-actuated robots 4

Finite-time neural network adaptive control of under-actuate...

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2014 4th International Conference on Mechanical engineering, Industry and Manufacturing engineering, MEIME 2014

作者： Wu, Zhong Qiang Liu, Li Ling Zhao, Li Ru Key lab of industrial computer control engineering of Hebei province Yanshan University China

ISBN: (纸本)9783038353256

The finite-time neural network adaptive control of under-actuated robot is investigated, and a kind of multistep control strategy is used. First the transformation of dynamics model is made, and the passive joints are driven to desire positions by the coupling among joints, then the passive joints are locked. When the passive joints are locked to other operating point, the system becomes the one with structure uncertain. Combining the theory of finite-time control with neural network adaptive control, a finite-time neural network adaptive controller is got which can make the position tracking of joint rapidly. The simulation shows the effectiveness of the controller. © (2014) Trans Tech Publications, Switzerland.

关键词： Robots

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Optimization of Tandem Cold Rolling Schedule Based on Competitive Coevolution Algorithm 33

Optimization of Tandem Cold Rolling Schedule Based on Compet...

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第三十三届中国控制会议

作者： ZHAO Xinqiu MENG Qinggang CHE Haijun YANG Jingming National Engineering Research Center for Equipment and Technology of Cold Strip Rolling Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University

ISBN: (纸本)9781479947249

The schedule set is an important part in the cold rolling process, which directly affects product quality and production efficiency in the production of steel rolling. Due to the low precision of traditional rolling force model, a model of rolling force was founded by the least squares support vector machine(LSSVM) method though analyzing the influencing factors of rolling force. Considering the diversity of optimization goal on rolling schedule of cold tandem rolling, the rolling schedule was optimized by competitive coevolution algorithm(Comp-CEA). A rolling schedule of steel cold rolling mill in Tangshan was optimized by selecting the power distribution, excellent flatness and the slip rate as objective functions. The experiment results show that Comp-CEA has the advantages such as high accuracy, rapid convergence and so on, and three objective functions can be improved in varying degrees.

关键词： Comp-CEA LSSVM,tandem cold rolling,rolling schedule

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An integrative study of home energy management for residential energy consumers

An integrative study of home energy management for residenti...

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IEEE International Conference on Cyber Technology in Automation, control, and Intelligent Systems

作者： Dong Zhang Peng Zeng Yanyu Zhang Shuhui Li State Grid Tianjin Electric Power Research Institute Tianjin China Key Lab. of Networked Control System Chinese Academy of Sciences Shenyang China Department of Electrical & Computer Engineering University of Alabama Tuscaloosa AL USA

This paper studies how to optimize the energy usage of home appliances in the demand response framework from the consumer's perspective. The loads of major home appliances are divided into three categories: fixed loads, regulate-able loads, and deferrable loads. For efficient usage of the home appliances, an integrative optimization of the three category loads is needed. The paper investigates the relation of the integrative optimization and individual optimization of each category load. A regression-based learning strategy is employed to learn HAVC energy consumption model for development of more efficient DR policy. The study is conducted through an integrative computational experiment approach that combines a home energy simulator and MATlab.together for demand response development and evaluation. The paper examines how the integrative demand response of the residential home appliances are affected by dynamic pricing tariffs, seasons, and weather. Case studies are conducted by considering home energy consumption, dynamic electricity pricing schemes, and demand response methods.

关键词： Home appliances Energy consumption Load modeling Optimization Load management Water heating Thermostats

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Game Theoretic Resource Allocation for Multicell D2D Communications with Incomplete Information

Game Theoretic Resource Allocation for Multicell D2D Communi...

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IEEE International Conference on Communications

作者： Jun Huang Ying Yin Yi Sun Yanxiao Zhao Cong-cong Xing Qiang Duan The State Key Lab. of Industrial Control Technology Zhejiang University School of CIE Chongqing University of Posts and Telecommunications ECE Department South Dakota School of Mines and Technology Department of Mathematics and Computer Science Nicholls State University IST Department The Pennsylvania State University

ISBN: (纸本)9781467364300

Resource allocation plays a critical role in implementing D2D communications underlaying a cellular network. Game-based approaches are recently proposed to address the resource allocation issue. Most existing approaches employ deterministic game models while implicitly assuming that each player in the game is completely willing to exchange transmission parameters with other players. Thus each player knows the complete information of all others. However, this assumption may not be satisfied in practice. For example, users may be reluctant to disclose all their parameters to peers. In this paper, we fully consider this scenario, i.e., players have incomplete information of others, and investigate the resource allocation problem for multicell D2D communications where a D2D link utilizes common resources of multiple cells. To attack this problem, a game-theoretic approach under the incomplete information condition is proposed. Specifically, we characterize the Base Stations (BSs) as players competing for resource allocation quota from the D2D demand, formulate the utility of each player as payoff from both cellular and D2D communications leasing the resources, and design the strategy for each player that is determined based on prior probabilistic payoff information of other players. We conduct extensive simulations to examine the proposed approach and the results demonstrate that the utility, sum rate, and sum rate gain of each player under the incomplete information condition are surprisingly higher than the counterparts under the complete information condition.

关键词： Games Resource management Bismuth Interference Uplink Game theory Mobile computing

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The study of terahertz time-domain spectroscopy of benzoyl peroxide 4

The study of terahertz time-domain spectroscopy of benzoyl p...

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4th International Conference on Advanced Design and Manufacturing engineering, ADME 2014

作者： Zhou, Zhi Long Chen, Xiai Han, Lu Zhang, Qing Hua Li, Xian School of Mechanical and Electrical Engineering China Jiliang University Hangzhou China State Key Lab. Of Industrial Control Technology Department of Control Science and Engineering Zhejiang University Hangzhou China

ISBN: (纸本)9783038352563

The spectral characteristics of benzoyl peroxide in the range of 0.3 to 1.6 in THz region is obtained by THz time-domain spectroscopy, the refraction and absorption spectra of benzoyl peroxide is got,meanwhile. The experimental result shows that, the benzoyl peroxide has the absorption peak at the wave band of 0.36621THz,0.498THz,0.92285THz,1.11328THz, the most obvious of which is at the wave band of *** terahertz absorption spectra of the mixture of flour and benzoyl peroxide is studied at the same *** experimental study provides a new method to detect benzoyl peroxide illegally added in food. © (2014) Trans Tech Publications, Switzerland.

关键词： Terahertz spectroscopy

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Distributed edge control for multi-agent based on binocular vision system

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Journal of Computational Information Systems 2014年第7期10卷 2907-2915页

作者： Shao, Nuan Li, Huiguang Zou, Liying Liu, Le Key Lab. of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao 066004 China

For multiple Lagrange systems, the objective of distributed edge control problem is to drive all the followers converge to the edge of the convex hull spanned by the leaders. In this approach, we choose binocular vision system as sensing devices. Firstly, a pseudo-stereo visual model is proposed based on the concept of depth information sensitivity which can be used to provide the generalized coordinates of the leaders for all followers in the image coordinate system. Then, based on this new model, a distributed adaptive control algorithm is designed to compensate for the parametric uncertainties under a directed graph. Finally, the proposed control algorithm is applied to the multi-manipulators grasping control, simulation examples are provided to show the effectiveness of the controller. © 2014 Binary Information Press.

关键词： Multi agent systems

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A double-loop structure in the adaptive generalized predictive control algorithm for control of robot end-point contact force

A double-loop structure in the adaptive generalized predicti...

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作者： Wen, Shuhuan Zhu, Jinghai Li, Xiaoli Chen, Shengyong Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao066004 China College of Computer Science Zhejiang University of Technology Hangzhou310023 China

Robot force control is an essential issue in robotic intelligence. There is much high uncertainty when robot end-effector contacts with the environment. Because of the environment stiffness effects on the system of the robot end-effector contact with environment, the adaptive generalized predictive control algorithm based on quantitative feedback theory is designed for robot end-point contact force system. The controller of the internal loop is designed on the foundation of QFT to control the uncertainty of the system. An adaptive GPC algorithm is used to design external loop controller to improve the performance and the robustness of the system. Two closed loops used in the design approach realize the systems performance and improve the robustness. The simulation results show that the algorithm of the robot end-effector contacting force control system is effective. © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： Point contacts

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