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14th World Congress on Intelligent Transport systems, ITS 2007

作者： Zhang, Kun Chen, Dewang Guan, Jizhen School of Electronics and Information Engineering Beijing Jiaotong University Beijing 100044 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing 10044 China Beijing STONE Intelligent Transportation System Integration Co. LTD. Beijing 100081 China

ISBN: (纸本)9781617387777

Current travel time prediction algorithms often need large numbers of travel time data, which are difficult to gain and highly cost, to identify the algorithms' parameters. In this paper, we propose new travel time prediction algorithms, which use neural network to predict future speed dynamically, and use data fusion to integrate the speed data of different detectors and, to calculate the travel time. Vehicle plate recognition technology is used to collect the real travel time of the test section on Beijing Third-Ring freeway to evaluate the algorithms. From the obtained results, the average prediction error is less than 10%.

关键词： Forecasting

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Chaos characteristic analysis on the time series of wend power generation capacity

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Taiyangneng Xuebao/Acta Energiae Solaris Sinica 2007年第11期28卷 1290-1294页

作者： Dong, Lei Gao, Shuang Liao, Xiaozhong Feng, Chengbo College of Information and Science Technology Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing 100081 China Internet Education School Xi'an Jiaotong University Xi'an 710049 China

The time series of wind power generating capacity were examined by nonlinear dynamical methods, in order to identify chaos characteristic from its random-like waveform. The analysis of modeling with low dimensions nonlinear dynamics indicated that time series of wind power generation capacity have chaos characteristic, and wind power generating capacity can be predicted in short time.

关键词： Wind power

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Research on energy efficiency of supercapacitor energy storage system

Research on energy efficiency of supercapacitor energy stora...

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2006 International Conference on Power system Technology, POWERCON2006

作者： Yun, Zhong Jiancheng, Zhang Gengyin, Li Aiguo, Liu Department of Electrical Power Engineering North China Electric Power University Baoding. Hebei 071003 China School of Information Engineering Nanchang University Nanchang Jiangxi 330029 China Key Laboratory of Power System Protection and Dynamic Security Monitoring and Control Ministry of Education North China Electric Power University Baoding 071003 Hebei Province China

ISBN: (纸本)1424401119

Recent developments in the field of supercapacitors have led to the achievement of high specific energy and high specific power devices which are suitable for energy storage in high power electronic applications, especially in the field of management of embarked electrical power. Equivalent serial resistance is put forward to estimate energy efficiency. Reducing the equivalent series resistance in a supercapacitor will gain a great appreciation. A supercapacitor energy storage system (SCESS) is also designed in this paper which is mainly composed of three parts: the electrical double-layer capacitors array that stores energy, the AC/DC-DC/AC power converter system and the integrated control system composed of microprocessors. This SCESS installed capacity is 0.235MJ;peak power is 5OkW;and generating efficiency is up to 97.94%. © 2006 IEEE.

关键词： Energy efficiency

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Research on Identifiability of Equivalent Motor in Composite Load Model

Research on Identifiability of Equivalent Motor in Composite...

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Power Tech Conference

作者： Ma Jin Han Dong He Renmu Dong Zhaoyang David J. Hill Key Laboratory of Power System Protection and Dynamic Security Monitoring and Control of Ministry of Education North China Electric Power University Beijing China School of Information Technology and the Electrical Engineering University of Queensland Saint Lucia QLD Australia Department of Information Engineering Australian National University Australia

Load modeling is very important for power system dynamic analysis and control. The composite load model widely applied recently in the power system operation centre consists of the static load and the equivalent motor. Current practices in measurement-based load modeling identify all the parameters in this composite load model. However, it is not clear whether all these parameters could be identified from the measurements. This paper investigates the identifiability of the equivalent motor parameters in the composite load model. Trajectory sensitivity approach is applied first to find the motor parameters that have great effects on the measured active as well as reactive load dynamics. The analysis results show that the motor outputs have various sensitivities with respect to the parameters. Since the voltage disturbance, the active load and the reactive load dynamics are applied to identify the motor parameters, those parameters affecting the measurements to a great extent are observable, thus identifiable from the measurements; while those that have little effects on the motor outputs are unobservable from the measurements and consequently unidentifiable. The case studies verify the identifiability of the motor parameters.

关键词： Load modeling Power system modeling Power system dynamics Power system simulation Power system stability Power system analysis computing Power system measurements Voltage Power system control Power systems

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Measurement-based Load Modeling using Genetic Algorithms

Measurement-based Load Modeling using Genetic Algorithms

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Congress on Evolutionary Computation

作者： Jin Ma Ren-mu He Zhao-yang Dong David J. Hill Key Laboratory of Power System Protection and Dynamic Secutitu Monitoring and Control of Ministy of Education North China Electric Power University Beijing China The School of Information Technology and Electrical Engineering University of Queensland QLD Australia The Department of Infotmation Engineering Australian National University Australia

Load modeling is very important to power system operation and control. Measurement-based load modeling has been widely practiced in recent years. Mathematically, measurement-based load modeling problem are closely related to the parameter identification area. Consequently, an efficient optimization method is needed to derive the load model parameters based on the feedback of estimation errors between the measurements and model outputs. This paper reports our work on applying genetic algorithms on measurement-based load modeling research. Due to its robustness to the initial guesses on the load model parameters, genetic algorithms are very suitable for load model parameter identification. Two cases including both the real measurement in a power station and the digital simulation are studied in the paper. For comparison purpose, the classical nonlinear least square estimation method is also applied to find the load model parameters. The simulated outputs from the load model confirm the efficiency of genetic algorithms in measurement-based load modeling analysis. Future work will focus on fastening the converging speed of the genetic algorithms, and/or utilizing more efficient evolutionary computation methods.

关键词： Load modeling Genetic algorithms Power system modeling Parameter estimation Power system measurements Power system control Power systems control system synthesis Area measurement Optimization methods

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Interactive Software Platform of Intelligent Supervisory control for the Mineral Grinding process

Interactive Software Platform of Intelligent Supervisory Con...

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IEEE Conference on control Technology and Applications (CCTA)

作者： Jinliang Ding Yang Cao Tianyou Chai Hong Wang Northeastern University Shenyang Liaoning CN Research Center of Automation Northeastern University Shenyang China Senior Member IEEE Key Laboratory of Integrated Automation of Process Industry (Northeastern University) Ministry of Education and Research Center of Automation Northeastern University Shenyang China. e-mail: tychai@*** Control System Centre University of Manchester Institute of Science and Technology UK

The mineral grinding process is an important procedure in the mineral processing. Its technical performance index is the particle size, which is closely related to the overall performance of the mineral processing. In this paper, we present the construction of a software platform of the supervisory control of the grinding process to control its particle size into the target range. The platform provides the researcher and the engineer with an interactive tool to investigate the supervisory control algorithms and their parameters selection. The supervisory control strategy, the structure and the function of the software platform are given in the paper, where two experiments are given to evaluate the software platform and the results show its validity and efficiency.

关键词： Intelligent control Supervisory control Minerals Ores control systems Size control process control Software algorithms Artificial intelligence Intelligent networks

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The integrated application of kriging method and 3D-GIS in digital mine

The integrated application of kriging method and 3D-GIS in d...

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11th International Congress for Mathematical Geology: Quantitative Geology from Multiple Sources, IAMG 2006

作者： Ma, Xiaogang Wu, Chonglong Zhang, Dan Wang, Kun Institute of Land and Resources Information System China University of Geosciences Wuhan 430074 Hubei China State Key Laboratory of Geological Process and Mineral Resources China University of Geosciences Wuhan Hubei 430074 China

ISBN: (纸本)9782960064407

Kriging method has been widely used in ore reserve calculation, while the 3DGIS has excellent ability in geological modelling and virtual reality. To realize the kriging reserve calculation in 3D-GIS and serve the subsequent mining plan, we designed the 3D block model to cooperate with the orebody model, surface model and mining model in 3DGIS. The geostatistical interpolation was applied in the block model and each block's attributes was quantified, such as the gold grade, rock type and specific density. The color and legend of each block was associated with its attributes. After the calculation, each block's attributes was filled in and the color was dynamically changed by the given cutoff grade. Then the block model could combine with orebody model to form conditional operators, and generate the underground mining design and reports of ore volume, quality or grade. It also could combine with the surface model to generate the optimized opencast mining design in given location. The 3D block model integrates advantages of both 3D-GIS and kriging method. It enhances the representation of the ore reserve calculation result, and comes to be the juncture of foregoing geological exploration and subsequent mining plan in the construction of Digital Mine.

关键词： Interpolation

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Modeling based on MOGA and the dynamic Ε -SVM for fermentation process

Modeling based on MOGA and the dynamic Ε -SVM for fermentat...

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6th World Congress on Intelligent control and Automation, WCICA 2006

作者： Xuejin, Gao Pu, Wang Chongzheng, Sun Yating, Zhang Huiqing, Zhang Yi, Jianqiang College of Electronic Information and Control Engineering Beijing University of Technology Beijing 100022 China Key Laboratory of Complex System and Intelligence Science Chinese Academy of Sciences Beijing 100033 China

ISBN: (纸本)1424403324

To found the suitable models to describe the behavior of biochemistry systems, the dynamic Ε -SVM method was proposed on the basis of SVM. Each training sample uses different error. The existed methods for selecting the parameters of SVM not only consume time, but also are difficult to find the optimal parameters. The optimal parameters were automatically decided by using multi-object Genetic Algorithm (MOGA). A new modeling method that combined MOGA with the dynamic Ε -SVM was presented. The model for penicillin titer preestimate was developed by it in Matlab6.5 with data collected from real plant. The model possesses the strong capability of fitting and generalization. Experiments show that the dynamic Ε -SVM is superior to the standard SVM modeling method. MOGA is very feasible and efficient too. ©2006 IEEE.

关键词： Fermentation

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Development of the Property of Four-Terminal Networks of Definite Structure and its Use in Bridge Circuits

Development of the Property of Four-Terminal Networks of Def...

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International Conference on Actual Problems of Electronic Instrument Engineering (APEIE)

作者： G.I. Peredelskiy Department of Automation Key Laboratory of System Control and Information Processing Shanghai China

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A quantum reinforcement learning method for repeated game theory

A quantum reinforcement learning method for repeated game th...

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2006 International Conference on Computational Intelligence and Security, ICCIAS 2006

作者： Chen, Chunlin Dong, Daoyi Dong, Yu Shi, Qiong Department of Control and System Engineering School of Management and Engineering Nanjing University Nanjing 210093 China Key Laboratory of Systems and Control Institute of Systems Science Chinese Academy of Sciences Beijing 100080 China Department of Information Management and Decision Science University of Science and Technology of China Hefei 230026 China College of Humanities and Social Science Anhui Medical University Hefei 230032 China

ISBN: (纸本)1424406056

In this paper, a quantum reinforcement learning method is proposed for repeated game theory. First, the quantum reinforcement learning algorithm is introduced based on quantum state superposition principle and its superiority is analyzed. Then, it is applied to repeated games and the experiments show its effectiveness. Related issues are also discussed before the conclusion is given. © 2006 IEEE.

关键词： Reinforcement learning

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