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IEEE International Conference on systems, Man and Cybernetics

作者： Leandro dos Santos Coelho Viviana Cocco Mariani Industrial and Systems Engineering Graduate Program-PPGEPS Automation and Systems Laboratory PUCPR/PPGEPS Pontifical Catholic University of Paraná Curitiba Parana Brazil Mechanical Engineering Graduate Program PUCPR/PPGEM Pontifical Catholic University of Paraná Curitiba Parana Brazil

Particle swarm optimization (PSO) is a population-based stochastic optimization technique, originally developed by Eberhart and Kennedy, inspired by simulation of a social psychological metaphor instead of the survival of the fittest individual. In PSO, the system (swarm) is initialized with a population of random solutions (particles) and searches for optima using cognitive and social factors by updating generations. PSO has been successfully applied to a wide range of applications, mainly in solving continuous nonlinear optimization problems. Based on the PSO and chaos theories, this paper discusses the use of a chaotic PSO approach hybridized with an implicit filtering (IF) technique to optimize performance of economic dispatch problems. The chaotic PSO with chaos sequences is the global optimizer and the IF is used to fine-tune the chaotic PSO run in sequential manner. The hybrid methodology is validated for a test system consisting of 13 thermal units whose incremental fuel cost function takes into account the valve-point loading effects.

关键词： Chaos Particle swarm optimization Fuel economy Stochastic processes Psychology Social factors Filtering theory System testing Thermal loading Cost function

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MODELING AND CONTROL OF ELEVATORS BY STATECHARTS

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Asian Journal of Control 2008年第2期6卷

作者： Yi-Sheng Huang Sheng-Luen Chung Mu-Der Jeng Department of Aeronautical Engineering Chung Cheng Institute of Technology National Defense University Tashi Taoyuan 335 Taiwan R.O.C. Department of Electrical Engineering National Taiwan University of Science and Technology Taipei 106 Taiwan R.O.C. Department of Electrical Engineering National Taiwan Ocean University Kellung 202 Taiwan R.O.C. MuDer Jeng received the Ph.D. degree in computer and systems engineering from Rensselaer Polytechnic Institute Troy NY in 1992. Since August 1992 Dr. Jeng has been with National Taiwan Ocean University Keelung Taiwan where he is currently a full Professor at the Department of Electrical Engineering. His current research interests include Petri nets discrete event systems computer integrated manufacturing semiconductor factory automation embedded systems. Dr. Jeng is the author/co-author of over 120 book chapters journal papers and conference papers. Dr. Jeng received the Franklin V. Taylor Outstanding Paper Award from the IEEE Systems Man and Cybernetics Society in 1993. He was granted the Research Award by the National Science Council of Taiwan annually from 1994 to 2000. He is an Associate Editor for IEEE Transactions on Systems Man and Cybernetics-Part A IEEE Transactions on Robotics and Automation IEEE Transactions on Robotics and serves on the Editorial Board of International Journal of Computer Integrated Manufacturing. He has been a Guest Editor for eight leading journals. Dr. Jeng is the Chair of the Technical Committee on Discrete Event Systems of the IEEE SMC Society and the Founding Chair of the Technical Committee on Semiconductor Factory Automation of the IEEE Robotics and Automation Society. He served as the Exhibitions Chair of 2003 IEEE International Conference on Robotics and Automation and the Special Sessions Chair of 2004 IEEE International Conference on Networking Sensing and Control. He serves as a Program Co-Chair of 2005 IEEE International Conference on Networking Sensing and Control and the Organization Commit

Statechart has been utilized as a visual formalism for the modeling of complex and interactive systems for its illuminating features on describing properties of causality, concurrency, and synchronization. This paper presents the application of satechart to the modeling, design and implementation of an elevator system, whose system behavior involves aggregating complexity of state descriptions, and imposition of underlying control policy. Based on the operational flow of an elevator, we derive the associated statechart model by looking into the inherent hierarchical structure of the elevator. The advantage of the proposed approach is the clear presentation of system behavior in terms of conditions and events that cause the transitions in system dynamics. Implementation of the controlled elevator based on the modeled statechart is also presented.

关键词： Statechart interactive systems elevator

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Combining of chaotic differential evolution and quadratic programming for economic dispatch optimization with valve-point effect (vol 21, pg 989, 2006)

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IEEE TRANSACTIONS ON POWER systems 2006年第3期21卷 1465-1465页

作者： dos Santos Coelho, Leandro Cocco Mariani, Viviana Production and Systems Engineering Graduate Program Automation and Systems Laboratory PUCPRJCCET/PPGEPSILAS Pontifical Catholic University of Paraná 802 15-901 Curitiba Paraná Brazil Mechanical Engineering Graduate Program PUCPRJCCETIPPGEM Pontifical Catholic University of Paraná 802 15-901 Curitiba Paraná Brazil

Evolutionary algorithms are heuristic methods that have yielded promising results for solving nonlinear, nondifferentiable, and multi-modal optimization problems in the power systems area. The differential evolution (DE) algorithm is an evolutionary algorithm that uses a rather greedy and less stochastic approach to problem solving than do classical evolutionary algorithms, such as genetic algorithms, evolutionary programming, and evolution strategies. DE also incorporates an efficient way of self-adapting mutation using small populations. The potentialities of DE are its simple structure, easy use, convergence property, quality of solution, and robustness. This paper proposes a new approach for solving economic load dispatch problems with valve-point effect. The proposed method combines the DE algorithm with the generator of chaos sequences and sequential quadratic programming (SQP) technique to optimize the performance of economic dispatch problems. The DE with chaos sequences is the global optimizer, and the SQP is used to fine-tune the DE run in a sequential manner. The combined methodology and its variants are validated for two test systems consisting of 13 and 40 thermal units whose incremental fuel cost function takes into account the valve-point loading effects. The proposed combined method outperforms other state-of-the-art algorithms in solving load dispatch problems with the valve-point effect. [ABSTRACT FROM AUTHOR]

关键词： Chaotic sequences differential evolution (DE) economic dispatch evolutionary algorithms optimization power generation valve-point effect

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MARKOV DECISION PROCESSES WITH UNCERTAIN TRANSITION RATES: SENSITIVITY AND MAX HYPHEN MIN CONTROL

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Asian Journal of Control 2008年第2期6卷

作者： Suresh Kalyanasundaram Edwin K. P. Chong Ness B. Shroff Motorola India Electronics Limited No. 66/1 Plot 5 Bagmane Techpark C. V. Raman Nagar Post Bangalore 560 093 India. Department of Electrical and Computer Engineering Colorado State University Fort Collins CO 80523-1373 USA. Professor Edwin K. P. Chong received the B.E.(Hons.) degree with First Class Honors from the University of Adelaide South Australia in 1987 graduating top of his class and the M.A. and Ph.D. degrees in 1989 and 1991 respectively both from Princeton University where he held an IBM Fellowship. He joined the School of Electrical and Computer Engineering at Purdue University in 1991 where he was named a University Faculty Scholar in 1999 and promoted to Full Professor in 2001. Since August 2001 he has been a Professor of Electrical and Computer Engineering and Professor of Mathematics at Colorado State University. His current interests are in communication networks and optimization methods. He coauthored the best-selling book An Introduction to Optimization 2nd Edition Wiley-Interscience 2001. He received the NSF CAREER Award in 1995 and the ASEE Frederick Emmons Terman Award in 1998. He coauthored a paper that was awarded Best Paper in the journal Computer Networks 2003. Professor Chong is a Fellow of the IEEE. He was founding chairman of the IEEE Control Systems Society Technical Committee on Discrete Event Systems and until recently served as an IEEE Control Systems Society Distinguished Lecturer. He has been on the editorial board of the IEEE Transactions on Automatic Control. He is currently on the editorial board of the journal Computer Networks. He has also served on the organizing committees of several international conferences. He has been on the program committees for the IEEE Conference on Decision and Control the American Control Conference the IEEE International Symposium on Intelligent Control IEEE Symposium on Computers and Communications and the IEEE Global Telecommunications Conference. He has also served in the executive committees for the IEEE Co

Solution techniques for Markov decision problems rely on exact knowledge of the transition rates, which may be difficult or impossible to obtain. In this paper, we consider Markov decision problems with uncertain transition rates represented as compact sets. We first consider the problem of sensitivity analysis where the aim is to quantify the range of uncertainty of the average per-unit-time reward given the range of uncertainty of the transition rates. We then develop solution techniques for the problem of obtaining the max-min optimal policy, which maximizes the worst-case average per-unit-time reward. In each of these problems, we distinguish between systems that can have their transition rates chosen independently and those where the transition rates depend on each other. Our solution techniques are applicable to Markov decision processes with fixed but unknown transition rates and to those with time-varying transition rates.

关键词： Markov decision processes sensitivity max-min control call admission control policy iteration

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Ramp metering based on adaptive critic designs

Ramp metering based on adaptive critic designs

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ITSC 2006: 2006 IEEE Intelligent Transportation systems Conference

作者： Xu, Jing Yu, Wen-Sheng Wang, Fei-Yue Institute of Automation Chinese Academy of Sciences Beijing 100080 China University of Arizonas Systems and Industrial Engineering Department Program in Advanced Research of Complex Systems Key Laboratory of Complex Systems and Intelligence Science Chinese Academy of Sciences

ISBN: (纸本)1424400945

This paper presents the technique of adaptive critic designs (ACDs) for resolving some traffic control problems, such as urban traffic signal control, ramp metering, highway speed control and so on. ACDs are adaptive optimal methods, whose main idea is to approximate dynamic programming solutions by using a function approximation structure such as neural networks to approximate the cost function or its derivatives. They combine the positive features of both the traditional dynamic programming (e.g., optimality and feedback) and the neural networks (e.g., numerical and real-time properties). Due to these exciting merits, they are promising in handling the traffic control problems which have strong nonlinear, stochastic and real-time characteristics. In this paper, a close look at two typical adaptive critic designs is conducted. Specifically, we demonstrate the use of a specific adaptive critic design for the local on-ramp metering control problem. Simulation results indicate that the proposed controller has good performance. © 2006 IEEE.

关键词： Traffic control

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Chaotic differential evolution applied to electromagnetics optimization

Chaotic differential evolution applied to electromagnetics o...

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12th Biennial IEEE Conference on Electromagnetic Field Computation, CEFC 2006

作者： Dos Santos Coelho, Leandro Mariani, Viviana Cocco Production and Systems Engineering Graduate Program Automation and Systems Laboratory Pontifical Catholic University of Paraná Imaculada Conceicao 1155 80215-901 Curitiba Brazil Pontifical Catholic University of Paraná Mechanical Engineering Graduate Program PUCPR/PPGEM Imaculada Conceicao 1155 80215-901 Curitiba Brazil

ISBN: (纸本)1424403200

This work presents a new global optimization algorithm based on differential evolution (DE) method and DE combined with chaotic sequences (DEC) given by logistic map. In this paper, the optimal shape design of Loney's solenoids benchmark problem is carried out by DE and DEC algorithms. The results of DE and DEC approaches are also investigated and their performance compared with those reported in the literature. © 2006 IEEE.

关键词： Chaos theory

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Electromagnetic device optimization using improved differential evolution methods

Electromagnetic device optimization using improved different...

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12th Biennial IEEE Conference on Electromagnetic Field Computation, CEFC 2006

作者： Coelho, Leandro Dos Santos Alotto, Piergiorgio Production and Systems Engineering Graduate Program Automation and Systems Laboratory Pontifical Catholic University of Paraná Imaculada Conccicao 1155 80215-901 Curitiba Paraná Brazil Dip. Ingegneria Eleurica University di Padova Italy

ISBN: (纸本)1424403200

Recently, evolutionary algorithms (e.g. genetic algorithms, evolutionary programming, and evolution strategies) have proven to be useful tools for the optimization of difficult problems in electromagnetics. Differential evolution (DE) is one comparatively simple variant of an evolutionary algorithm using floating-point encoding and few control parameters. This work presents improved DE algorithms based on linearly time varying control parameters, sinusoidal functions, and diversity analysis of population. © 2006 IEEE.

关键词： Electromagnets

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Use of cultural particle swarm optimization for Loney's Solenoids design

Use of cultural particle swarm optimization for Loney's Sole...

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12th Biennial IEEE Conference on Electromagnetic Field Computation, CEFC 2006

作者： Coelho, Leandro Dos Santos Mariani, Viviana Cocco Pontifical Catholic University of Paraná Production and Systems Engineering Graduate Program Automation and Systems Laboratory PUCPR/PPGEPS/LAS Imaculada Conceicao 1155 80215-901 Curitiba Brazil Pontifical Catholic University of Paraná Mechanical Engineering Graduate Program PUCPR/PPGEM Imaculada Conceiçao 1155 80215-901 Curitiba Brazil

ISBN: (纸本)1424403200

This work presents the use of particle swarm optimization (PSO) techniques with the particles' population space based on normative knowledge of cultural algorithms (CA). In this work, the optimal shape design of Loney's solenoids benchmark problem is carried out by PSO, PSO-CA, Gaussian PSO and Gaussian PSO-CA approaches. ©2006 IEEE.

关键词： Solenoids

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An efficient particle swarm optimization approach based on cultural algorithm applied to mechanical design

An efficient particle swarm optimization approach based on c...

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2006 IEEE Congress on Evolutionary Computation, CEC 2006

作者： Dos Coelho, Leandro Santos Mariani, Viviana Coceo Pontifical Catholic University of Paraná Production and Systems Eng. Graduate Program Automation and Systems Laboratory Imaculada Conceicao 1155 80215-901 Curitiba Parana Brazil Pontifical Catholic University of Paraná Mechanical Engineering Graduate Program Imaculada Conceicao 1155 80215-901 Curitiba Parana Brazil

ISBN: (纸本)0780394879

Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm driven by the simulation of a social psychological metaphor instead of the survival of the fittest individual. Based on the swarm intelligence theory, this paper discusses the use of PSO approaches using an operator and based on the Gaussian probability distribution function as a population space of a cultural algorithm, called cultural Gaussian PSO (GPSO-CA). Cultural algorithms are mechanisms that incorporate domain knowledge obtained during the evolutionary process, which increase the efficiency of the search process. These approaches are employed in a well-studied continuous optimization problem of mechanical engineering design. © 2006 IEEE.

关键词： Global optimization

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Modeling and analysis of artificial transportation system based on multi-agent technology

Modeling and analysis of artificial transportation system ba...

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ITSC 2006: 2006 IEEE Intelligent Transportation systems Conference

作者： He, Feng Miao, Qinghai Li, Yuantao Wang, Fei-Yue Tang, Shuming IEEE Key Laboratory for Complex Systems and Intelligence Science Chinese Academy of Sciences Beijing China Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences CO 100080 Beijing China Program for Advanced Research in Complex Systems Department of Systems and Industrial Engineering University of Arizona Tucson AZ 85719 United States Institute of Automation Shandong Academy of Sciences Jinan 250014 China

ISBN: (纸本)1424400945

This paper presents the multi-agent architecture for artificial transportation system. In this architecture, Petri net is used as basic model to represent agents. At an intersection, the agents are divided into two groups: one for the traffic-signal and the other for the vehicle flow, which are integrated to represent the behavior of this intersection. In addition, those agents can be used as the modularity to represent urban network of more scale. To coordinate different intersection agents, game theory is used to design coordination strategy between agents. The iterated elimination of strictly dominated strategies algorithm is presented to find Nash equilibrium. © 2006 IEEE.

关键词： Transportation

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