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NON-LINEAR PREDICTIVE CONTROLLERS FOR THERMAL COMFORT OPTIMIZATION AND ENERGY SAVING

IFAC Proceedings Volumes 2006年第19期39卷 87-92页

作者： Roberto Z. Freire Gustavo H.C. Oliveira Nathan Mendes Industrial and Systems Engineering Graduate Program - PPGEPS Thermal Systems Laboratory - LST Pontifical Catholic University of Parana Curitiba/PR/Brazil - Zip Code 80215-901

The present work is focused on the study of indoor thermal comfort control problem in buildings equipped with heating systems. The occupants' thermal comfort sensation is addressed here by a comfort index known as PMV (Predict Mean Vote). In this context, two control algorithms are proposed by using only-one-actuator system associated to the heating system. The methods are based on the model predictive control scheme and on the improvement of the PMV index together with energy minimization. Simulation results - obtained by using the weather data file for the city of Curitiba, Brazil - for two case studies: i ) variations between low and moderate occupants metabolic rates and ii) variations between moderate and high occupants metabolic rates are presented to validate the proposed methodology in terms of room air temperature, relative humidity and PMV control.

关键词： predictive control thermal comfort heating systems non-linear control

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Editorial

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Journal of Scheduling 2006年第3期9卷 199-201页

作者： Bard, Jonathan F. Barnhart, Cynthia Graduate Program in Operations Research The University of Texas Austin USA Civil & Environmental Engineering and Engineering Systems Massachusetts Institute of Technology Cambridge USA

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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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IEEE Conference on Electromagnetic Field Computation

作者： L. dos Santos Coelho V. Cocco Mariani Production and Systems Engineering Graduate Program Automation and Systems Laboratory PUCPR/PPGEPS/LAS Pontifical Catholic University of Paraná Curitiba Brazil Mechanical Engineering Graduate Program PUCPR/PPGEM Pontifical Catholic University of Paraná Curitiba Brazil

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 L... 详细信息

关键词： Cultural differences Particle swarm optimization Solenoids Optimization methods Design optimization Algorithm design and analysis Gaussian distribution Probability distribution Random number generation Equations

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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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Congress on Evolutionary Computation

作者： L. dos Santos Coelho V.C. Mariani Production and Systems Engineering Graduate Program Automation and Systems Laboratory PPGEPS/CCET/PUCPR Pontifical Catholic University of Paraná Curitiba Parana Brazil Mechanical Engineering Graduate Program Pontifical Catholic University of Paraná Curitiba Parana Brazil

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.

关键词： Particle swarm optimization Cultural differences Algorithm design and analysis Probability distribution Design optimization Equations Design engineering Mechanical engineering Random number generation Psychology

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Neural Networks, Fuzzy System, and Linear Models in Forecasting Exchange Rates: Comparison and Case Studies

Neural Networks, Fuzzy System, and Linear Models in Forecast...

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International Joint Conference on Neural Networks (IJCNN)

作者： A.A.P. Santos L. dos Santos Coelho Graduate Program in Economics Federal University of Santa Catarina Santa Catarina Brazil Production and Systems Engineering Graduate Program Automation and Systems Laboratory PPGEPS/CCET/PUCPR Pontifical Catholic University of Paraná Parana Brazil

Artificial neural networks and fuzzy systems, have gradually established themselves as popular tools in approximating complicated nonlinear systems and time series forecasting. This paper investigates the hypothesis that the nonlinear mathematical models of multilayer perceptron and radial basis function neural networks and the Takagi-Sugeno (TS) fuzzy system are able to provide a more accurate out-of-sample forecast than the traditional autoregressive moving average (ARMA) and ARMA generalized autoregressive conditional heteroskedasticity (ARMA-GARCH) linear models. Using series of Brazilian exchange rate (R$/US$) returns with 15 min., 60 min., 120 min., daily and weekly basis, the out-pf-sample one-step-ahead forecast performance is compared. Results indicate that forecast performance is strongly related to the series' frequency and the forecasting evaluation shows that nonlinear models perform better than their linear counterparts. In the trade strategy based on forecasts, nonlinear models achieve higher returns when compared to a buy-and-hold strategy and to the linear models.

关键词： Neural networks Fuzzy systems Predictive models Exchange rates Autoregressive processes Artificial neural networks Mathematical model Nonlinear systems Multilayer perceptrons Radial basis function networks

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Development of drug carriers for therapy of arterioscleosis

Development of drug carriers for therapy of arterioscleosis

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55th Society of Polymer Science Japan Symposium on Macromolecules

作者： Ikuta, Kenjiro Mori, Takeshi Niidome, Takuro Shimokawa, Hiroaki Katayama, Yoshiki Graduate School of Systems Life Sciences Kyushu University 744 Motooka Nishi-ku Fukuoka 819-0395 Japan Faculty of Engineering Kyushu University CREST-JST Center for Future Chemistry Kyushu University Grant-in-Aid for the 21St Century COE Program Graduate School of Medical Science Tohoku University

The vascular endothelium dysfunction often leads to a cardiovascular disease such as arteriosclerosis. Therefore, detection and evaluation of vascular endothelium disorder in early stage would be very important for the effective diagnosis and therapy. We found that the structural analogues of Evans Blue adsorb to a vascular endothelium denuded region. Thus, we synthesized a polymeric drug carrier which consisted of amphipathic polymer and sensing unit (Evans Blue analogue) and evaluated the characteristics of the polymeric carriers. And then a extracted porcine aorta which was removed endothelial cell in left half area was treated with the micelle solution to evaluate a targeting ability of the micelle.

关键词： Controlled drug delivery

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Nonlinear System Identification Based on B-Spline Neural Network and Modified Particle Swarm Optimization

Nonlinear System Identification Based on B-Spline Neural Net...

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International Joint Conference on Neural Networks (IJCNN)

作者： L. dos Santos Coelho R.A. Krohling Production and Systems Engineering Graduate Program Automation and Systems Laboratory PPGEPS/CCET/PUCPR Pontifical Catholic University of Paraná Parana Brazil Chair for Control Systems Engineering RST Faculty of Electrical Engineering and Information Technology University of Dortmund Dortmund Germany

Artificial neural networks, in particular, feedforward multilayer networks and basis function networks, have gradually established themselves as a usual tool in approximating complex nonlinear systems. B-spline networks, a type of basis function neural network, are normally trained by gradient-based methods, which may fall into local minima during the learning phase. In order to overcome the drawbacks encountered by conventional learning methods, particle swarm optimization - a swarm intelligence methodology - can provide a stochastic global search of B-spline networks for nonlinear system identification. In this paper, a modified particle swarm optimization algorithm using Gaussian and Cauchy probability distributions are applied to adjust the control points of B-spline neural networks. Simulation results for the identification of Rossler systems are provided and demonstrate the effectiveness and robustness of the proposed identification scheme.

关键词： Nonlinear systems Spline Neural networks Particle swarm optimization Artificial neural networks Multi-layer neural network Learning systems Stochastic systems Probability distribution Robustness

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Design and prototype development of advanced oxidation black and gray water treatment systems

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NAVAL ENGINEERS JOURNAL 2006年第3期118卷 51-64页

作者： Markle, Stephen P. CDR. STEPHEN P. MARKLE USN (REt.)P.E.a retired US Navy Engineering Duty Officer and is the Engineering Director for Navalis Environmental Systems. His active duty assignments included the staff of the Chief of Naval Operations Director of Surface Warfare as Section Head for Surface Combatant Maintenance and Modernization Program Executive Office Expeditionary Warfare as Assistant Project Manager for the (TAKE 1)Class Program and as Deputy Director Environmental Programs Division at Naval Sea Systems Command. He is a 1993 graduate of the Naval Construction and Engineering Program at the Massachusetts Institute of Technology where he received a Naval Engineers Degree and Master of Science in Mechanical Engineering. Since 1995 he has authored thirteen published technical papers dealing with environmental issues. CDR Markle is the recipient of Fiscal Year 2001 Individual Environmental Quality Awards and Environmental Excellence in Weapon System Acquisition Team Awards from Naval Sea Systems Command Chief of Naval Operations Secretary of the Navy and Secretary of Defense and the 2001 ASNE “Jimmie Hamilton” award. He is a Professional Engineer registered in the State of New York and Commonwealth of Virginia. He serves as the Chair of the Joint ASNE/SNAME Committee on Environmental Engineering and also as Chair of ASTM Ships and Marine Technology Marine Environmental Protection Subcommittee (F25.06).

Regulations governing the discharge of sewage from ships have been in force since the early 1970's. In response, the marine industry has developed ever more complex systems and processes for managing these wastes. The first compliance method involved holding wastes until they could be legally discharged;as technology advanced, treatment systems were developed and installed to enable discharge within regulated waters. As the size and number of ships as increased with maturation of the ocean tourism business, more restrictive regulations have been enacted to minimize the impact on sensitive waters. The trend is toward increasing regulation of both sewage and graywater. The most recent action occurred on 12 October 2005 when the Governor of California signed into law Senate Bill 771 regulating most ship liquid discharges within state waters. This paper describes the development of an innovative advanced wastewater treatment technology, based on advanced oxidation, bearing in mind the lessons learned from systems developed by industry over the past thirty years.

关键词： Wastewater treatment

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Supply Chain Optimization Using Chaotic Differential Evolution Method

Supply Chain Optimization Using Chaotic Differential Evoluti...

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IEEE International Conference on systems, Man and Cybernetics

作者： Leandro dos Santos Coelho Heitor Silverio Lopes Production and Systems Engineering Graduate Program Automation and Systems Laboratory Pontifical Catholic University of Paraná Curitiba Parana Brazil UTFPR/CPGEI Federal Technological University of Parana Curitiba Parana Brazil

This paper describes the application of differential evolution approaches to the optimization of a supply chain. Although simplified, this supply chain included stocks, production, transportation and distribution, in an integrated production-inventory-distribution system. The supply chain problem model is presented as well as a short introduction to each evolutionary algorithm. Differential evolution (DE) is an emergent evolutionary algorithm that offers three major advantages: it finds the global minimum regardless of the initial parameter values, it involves fast convergence, and it uses few control parameters. Inspired by the chaos theory, this work presents a new global optimization algorithm based on different DE approaches combined with chaotic sequences (DEC), called chaotic differential evolution algorithm. The performance of three evolutionary algorithm approaches (genetic algorithm, DE and DEC) and branch and bound method were evaluated with numerical simulations. Results were also compared with other similar approach in the literature. DEC was the algorithm that led to better results, outperforming previously published solutions. The simplicity and robustness of evolutionary algorithms in general, and the efficiency of DEC, in particular, suggest their great utility for the supply chain optimization problem, as well as other logistics-related problems.

关键词： Supply chains Optimization methods Chaos Evolutionary computation Production systems Transportation Convergence Genetic algorithms Numerical simulation Robustness

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Chaotic Differential Evolution Applied to Electromagnetics Optimization

Chaotic Differential Evolution Applied to Electromagnetics O...

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IEEE Conference on Electromagnetic Field Computation

作者： L. dos Santos Coelho V.C. Mariani Production and Systems Engineering Graduate Program Automation and Systems Laboratory PUCPR/PPGEPS/LAS Pontifical Catholic University of Paraná Curitiba Brazil PUCPR/PPGEM Pontifical Catholic University of Paraná Curitiba Brazil

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

关键词： Chaos Solenoids Optimization methods Evolutionary computation Stochastic processes Genetic mutations Logistics Algorithm design and analysis Design optimization Electronic mail

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