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NEURAL-ADAPTIVE control BASED ON ADALINE NEURONS WITH APPLICATION TO A POWER system

IFAC Proceedings Volumes 2007年第18期40卷 457-464页

作者： Ioan Filip Octavian Prostean Florin Dragan Cristian Vasar Department of Control System Engineering “Politehnica” University from Timisoara Faculty of Automation and Computer Science 300223 Timisoara Romania Phone: (+40) 0256-403238 E-Mail: ioan.filip@aut.upt.ro

A neural-adaptive control solution is exposed in this paper. The control strategy is based on the linear adaptive neuron, which is called ADALINE. Unlike other neural control solutions, based on perceptrons neurons characterized by a long time learning process and a difficult on-line tuning of weights, this approach uses a fast algorithm, which adapts on-line the neuron's weights. Therefore the non-linear character of control law is induced by the permanent changes of neuron weights, which are variable parameters of controller. A set of study cases is done, with application to the excitation control of a synchronous generator.

关键词： adaptive control neural networks ADALINE modelling simulation synchronous generator

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SHORT TERM ELECTRIC LOAD FORECAST WITH ARTIFICIAL NEURAL NETWORKS

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IFAC Proceedings Volumes 2007年第18期40卷 443-449页

作者： Vasar Cristian Szeidert Iosif Filip Ioan Prostean Gabriela Department of Control System Engineering “Politehnica” University from Timisoara Faculty of Automation and Computer Science 300223 Timisoara Romania Phone: (+40) 256-403237 E-Mail: cristian.vasar@aut.upt.ro

This paper presents issues regarding short term electric load forecasting using feedforward and Elman recurrent neural networks. The study cases were developed using measured data representing electrical energy consume from Banat area. There were considered 35 different types of structure for both feedforward and recurrent network cases. For each type of neural network structure were performed many trainings and best solution was selected. The issue of forecasting the load on short term is essential in the effective energetic consume management in an open market environment.

关键词： neural networks prediction problems load forecasting feedforward networks simulation

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ML DESIGNERTM as simulation tool in robotics

ML DESIGNERTM as simulation tool in robotics

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International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Service (TELSIKS)

作者： Mario Schulz Ivan Velickovic Sasa Andelkovic Volker Zerbe Goran S. Dordevic Computer Science and Automation Faculty System and Control Theory Department Technical University Ilmenau Ilmenau Germany Faculty of Electronics engineering Robotics Lab University of Nis Nis Serbia

Robots are complex systems that require multidisciplinary approach to development. Hence, both research and production of a robotic system require a tool that would provide means for coordination between teams with different areas of expertise as well as the ability to integrate, simulate and debug the system in a comprehensive way. Also, with the growing popularity of service robotics, research and modeling of human-machine interaction gains the attention. From a simulation tool, it is expected to support the means for describing this interaction. For that purpose we are investigating the ML Designer TM , not just as a possible simulation tool, but also as a modeling and design paradigm. For verification purposes we will compare it against MATLAB Simulink TM . A pneumatic system will be modeled with both tools and a comparison will be performed.

关键词： Mathematical model Robot kinematics Cleaning system testing Power system modeling MATLAB Pneumatic systems control systems Level control Costs

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Dynamic Event Analysis using Synchronized PMUs via 220V Wall Outlets

Dynamic Event Analysis using Synchronized PMUs via 220V Wall...

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2007 International Power engineering Conference (IPEC2007), vol.2

作者： Issarachai Ngamroo Panlert Lappanakul Nitus Voraphonpiput Sanchai Dechanupaprittha Yasunori Mitani Jareerat Sakulrat Department of Electrical Engineering Faculty of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Power System Analysis Department Control and Protection Electricity Generating Authority of Thailand Thailand Department of Electrical Engineering Kyushu Institute of Technology Fukuoka Japan Department of Civil Engineering Prince of Songkla University Songkla Thailand

This paper presents the dynamic analysis results of a system event in Thailand power network using a wide-area monitoring system based on synchronized phasor measurement units (PMUs). The salient feature of the proposed monitoring system is the convenient installation of PMU at 220V wall power outlets. The event considering here is a 80MW load transferring from Thailand to Malaysia systems through a weak 115kV tie-line. To perform load transferring, a synchronization between both systems is required. This causes a problem of frequency osculation in a southern area of Thailand. Besides, this event severely excites the inter-area oscillation in a 230kV tie-line between central and southern areas of Thailand. Analyzed results based on discrete wavelet decomposition and short-time Fourier Transform provide valuable information of the system dynamic behavior in both frequency and time domains.

关键词： Synchronized Phasor measurement units Wide-area monitoring Inter-area oscillation Discrete wavelet decomposition Least-squares regression Short-time Fourier Transform

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Combined Use of Fuzzy Set-Covering Theory and Mode Identification Technique for Fault Diagnosis in Power systems

Combined Use of Fuzzy Set-Covering Theory and Mode Identific...

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2007 IEEE Power engineering Society General Meeting (PES 2007), vol.6

作者： Jian Xiao Fushuan Wen Key Laboratory of Power System Protection and Dynamic Security Monitoring and Control (North China Electric Power University) Ministry of Education Beijing China Department of Electrical Engineering South China University of Technology Guangzhou China

After a fault occurs in a power system, generally some operating information of protective relays and circuit breakers could be obtained. Because protective relays and circuit breakers might improperly operate or fail to operate, and some errors and distortion may exist in data acquisition and communication, as a result uncertainties could be involved in the received information. A fault diagnosis model based on fuzzy set-covering theory and mode identification technique is proposed in this paper. With the fuzzy technology, the above mentioned uncertainties could be dealt with very well. Meanwhile, as the protective relays and circuit breakers may fail to operate in some cases, there are several different operating modes in protective relays and circuit breakers even for a same electrical device failure. Based on the received information, the proposed model could identify the most possible operating mode, and then the information corresponding to a fault hypothesis could be obtained. In the proposed model, the proposed fault diagnosis problem is described as a 0-1 integer programming one, and thus could be solved by the widely employed search technology, i.e., the well-known Tabu search method. The feasibility and efficiency of the proposed model is demonstrated by a sample power system.

关键词： Fault Diagnosis Fuzzy Sets Set-Covering Theory Mode Identification Technique

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Power system Restoration in Restructured Power Industry

Power System Restoration in Restructured Power Industry

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2007 IEEE Power engineering Society General Meeting (PES 2007), vol.6

作者： Zhenzhi Lin Fushuan Wen Key Laboratory of Power System Protection and Dynamic Security Monitoring and Control under Ministry of Education North China Electric Power University Beijing China Department of Electrical Engineering South China University of Technology Guangzhou China

Power system restoration decision-making is one of the most important and indispensable issues for ensuring fast power supply restoration to end users. In recent years, the power industry around the globe has been undertaking an in-depth restructuring, and this has led to some new challenges to the problem of power system restoration. In this paper, several important issues related to power system restoration in the traditional power industry and in the electricity market environment are analyzed and compared, and then the impacts of the restructuring efforts on the power system restoration are identified and clarified from several aspects including black-start, restoration tests, dispatching and distribution system service restoration. Up to now, in most of the practically operating electricity markets around the globe power system restoration ancillary service is still based on cost compensation rather than market mechanism.

关键词： Electricity market Power system restoration Black-start Distribution system service restoration

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A Study On Iterative Learning control With Adjustment Of Learning Interval For Monotone Convergence In The Sense Of Sup-Norm

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Asian Journal of control 2008年第1期4卷

作者： Kwang-Hyun Park Zeungnam Bien Division of EE Department of EECS Korea Advanced Institute of Science and Technology 373–1 Kusong-dong Yusong-gu Taejon 305–701 Korea. Zeungname Bien:received the B.S. degree in electronics engineering from Seoul National University Seoul Korea in 1969 and the M.S. and Ph.D. degrees in electrical engineering from the University of Iowa Iowa City Iowa U.S.A. in 1972 and 1975 respectively. During 1976–1977 academic years he taught as assistant professor at the Department of Electrical Engineering University of Iowa. Then Dr. Bien joined Korea Advanced Institute of Science and Technology summer 1977 and is now Professor of Control Engineering at the Department of Electrical Engineering and Computer Science KAIST. Dr. Bien was the president of the Korea Fuzzy Logic and Intelligent Systems Society during 1990–1995 and also the general chair of IFSA World Congress 1993 and for FUZZ-IEEE99 respectively. He is currently co-Editor-in-Chief for International Journal of Fuzzy Systems (IJFS) Associate Editor for IEEE Transactions on Fuzzy Systems and a regional editor for the International Journal of Intelligent Automation and Soft Computing. He has been serving as Vice President for IFSA since 1997 and is now Chief Chairman of Institute of Electronics Engineers of Korea and Director of Humanfriendly Welfare Robot System Research Center. His current research interests include intelligent control methods with emphasis on fuzzy logic systems service robotics and rehabilitation engineering and large-scale industrial control systems. Kwang-Hyun Park:received the B.S. M.S. and Ph.D. degrees in electrical engineering and computer science from KAIST Korea in 1994 19997 and 2001 respectively. He is now a researcher at Human-friendly Welfare Robot System Research Center. His research interests include learning control machine learning human-friendly interfaces and service robotics.

It has been found that some huge overshoot in the sense of sup-norm may be observed when typical iterative learning control (ILC) algorithms are applied to LTI systems, even though monotone convergence in the sense of λ-norm is guaranteed. In this paper, a new ILC algorithm with adjustment of learning interval is proposed to resolve such an undesirable phenomenon, and it is shown that the output error can be monotonically converged to zero in the sense of sup-norm when the proposed ILC algorithm is applied. A numerical example is given to show the effectiveness of the proposed algorithm.

关键词： Iterative learning control monotone convergence learning interval sup-norm

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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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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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Robust quadratic optimal control of uncertain TS-fuzzy-model-based dynamic systems

Robust quadratic optimal control of uncertain TS-fuzzy-model...

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IEEE International Conference on systems, Man and Cybernetics

作者： Wen-Hsien Ho Jinn-Tsong Tsai Tung-Kuan Liu Jyh-Horng Chou Department of Medical Information Management Kaohsiung Medical University Taiwan Department of Computer Science National Ping Tung University of Education Taiwan Department of Mechanical and Automation Engineering National Kaohsiung First University of Science and Technology Taiwan Institute of System Information and Control National Kaohsiung First University of Science and Technology Kaohsiung Taiwan

This paper considers the design problem of the robust quadratic-optimal parallel-distributed-compensation (PDC) controllers for the Takagi-Sugeno (TS) fuzzy-model- based control systems with both elemental parametric uncertainties and norm-bounded approximation error. An integrative method, which complementarily fuses the robust stabilizability condition, the orthogonal-functions approach (OFA) and the hybrid Taguchi-genetic algorithm (HTGA), is presented in this paper to design the robust quadratic-optimal PDC controllers, in which the robust stabilizability condition is proposed in terms of linear matrix inequalities (LMIs).

关键词： Robust control Optimal control Nonlinear control systems control systems Uncertainty Approximation error Fuzzy control Fuzzy systems Algorithm design and analysis Nonlinear dynamical systems

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