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Integration, participation and optimal control in water resources planning and management

APPLIED MATHEMATICS AND COMPUTATION 2008年第1期206卷 21-33页

作者： Castelletti, Andrea Pianosi, Francesca Soncini-Sessa, Rodolfo Politecn Milan Dipartimento Elettron & Informaz I-20133 Milan Italy

Water resource systems provide a challenging testing ground for System Analysis and Optimal Control Theory. The intrinsic complexity of the physical system, which is highly non-linear and affected by strong uncertainty, intermingles with the value-laden socio-economic context in which decisions on the systems have to be taken. Mathematical models and algorithms have to be re-considered within a methodological framework, in which stakeholder participation and cross-disciplinary approaches are given a central role. In this paper the Integrated and Participatory Planning ( PIP) procedure developed by the authors is presented as a potential methodological approach to the effective and efficient planning and management of water systems. Great emphasis is given to the way to combine traditional control techniques with preference and subjective aspects of decision-making. The key role of multi-objective Decision Support Systems (MODSS) is also stressed as a way of bridging the gap between theory and practice. (c) 2007 Elsevier Inc. All rights reserved.

关键词： Water resources management Stochastic optimal control Adaptive control multi-objective optimization Decision support system

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Digital PID Controller Design Based on Parametric optimization

Digital PID Controller Design Based on Parametric Optimizati...

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IEEE International Conference on Control Applications

作者： Gambier, Adrian Heidelberg Univ Automat Lab D-68131 Mannheim Germany

ISBN: (纸本)9781424422227

PID control is probably the most applied control strategy around the world. There is also a huge amount of literature available about this control strategy. In the most common case, the controller is formulated in the continuous-time domain. If it is necessary to implement the controller as a computational algorithm, controller's equations are discretized. It is less frequent to find PID control laws, which are directly formulated as a discrete-time system. It is also possible, but unusual, to find design methods for digital PID controllers based on parametric optimization. Therefore, the objective of this paper is to revisit the digital PID/PI controller design based on parametric optimization including new advanced optimization methods as well as taking into consideration the new calculation machinery for several performance indices. Single as well as multi-objective optimization approaches are considered. Finally, available software and practical implementation aspects are highlighted.

关键词： Three term control systems

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Pareto optima and Nash equilibria - An effective approach to the shape design in electromagnetics

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COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING 2008年第4期27卷 845-854页

作者： Cioffi, M. Di Barba, P. Formisano, A. Martone, R. Seconda Univ Napoli Dipartimento Ingn Informaz Aversa Italy Consorzio CRIS Naples Italy Univ Pavia Dept Elect Engn I-27100 Pavia Italy

Purpose - This paper seeks to describe an approach to multi-objective optimization problems (MOOPs) based on game theory (GT) and to provide a comparison with the more standard Pareto approach on a real design problem. Design/methodology/approach - The GT is first briefly presented, then a possible recasting of MOOPs in terms of GT is described, where players from GT are associated with single objectives and strategies to the choice of degrees of freedom. A comparison with the Pareto approach is performed on the optimized design of a superconducting synchronous generator. Findings - It was shown that the GT can be applied to the optimized design of real world devices, with results that present a different viewpoint on the problem, yet with device performance comparable with those obtained by standard approaches. Research limitations/implications - Only the Nash approach to non-cooperative games has been applied;the conditions for the solution found using GT to belong to the Pareto front have not been fully explored. practical implications - Designers and engineers interested in optimal design are presented with a new design technique able to get a balance among conflicting partial objectives, that can also be used to select among different possible designs obtained in other ways (e.g. using the Pareto front approach). Originality/value - The paper demonstrates the possibility of using GT in the design of real world electromagnetic devices, with reference to the optimal shape design of a high temperature superconducting single-phase synchronous generator.

关键词： game theory optimization techniques design electric generators

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optimization of biventricular pacing for the treatment of acute ventricular dysfunction

Optimization of biventricular pacing for the treatment of ac...

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作者： Quinn, Thomas Alexander Columbia University

学位级别：Ph.D.

Permanent biventricular pacing (BiVP), or cardiac resynchronization therapy, is an effective treatment for patients with congestive heart failure. Acute and long-term benefits to ventricular systolic and diastolic function have been observed, with no cost to myocardial energy consumption. This suggests that BiVP may also be useful as an adjunctive treatment for acute ventricular dysfunction commonly seen after cardiac surgery. In both the chronic and acute setting, it has been shown that optimization of pacing parameters can improve the efficacy of BiVP. However, there is little understanding of BiVP optimization, and protocols remain complex, time consuming, and unreliable. Better understanding of the effects of BiVP optimization on hemodynamics, along with techniques for simpler and faster optimization, is desperately needed. Thus, the main objective of this dissertation was to better understand the effects of optimizing temporary BiVP during acute heart failure and to develop methods for making its use practical for perioperative treatment. The effects of varying BiVP timing and pacing site on cardiac output, ventricular contractility, mechanical synchrony, and QRS duration were assessed in animal models of acute ventricular dysfunction and in patients after cardiac surgery. Novel approaches included a custom temporary, external biventricular pacing system and a multi-electrode, temporary, epicardial pacing array for both animal and clinical use, custom hemodynamic analysis algorithms, arterial waveform analysis with the PulseCO system, real-time hemodynamic analysis of BiVP effects, and intelligent optimization schemes. In animal models of acute right and left ventricular failure, it was found that optimization could improve cardiac function, and that optimum settings depended on the specific pathology. Furthermore, it was shown that simultaneous parameter optimization was often necessary to obtain the greatest benefit due to parameter interaction. It was also d

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Pareto optimization of grillage system with multi-objective

Pareto optimization of grillage system with multi-objective

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2008建模、辨识与控制国际会议

作者： Yunyoung Kim Byeong-Il Kim Joo-Shin Park Department of Naval Architecture & Ocean Engineering Mokpo National Maritime University Department of Naval Architecture & Ocean Engineering Osaka University

Many real-world design problems involve simultaneous optimization of multiple objectives. The considered grillage design is a multi-objective optimization problem, since there are two objective functions, namely, the volume design and the cost design. Thus, the solution of this optimization problem requires specialized method suitable for multi-objective problems. In this article, a multi-objective design optimization using real-coded genetic algorithm which is proposed for the Pareto-optimality of grillage system. The objective functions in the optimization problem measure the design sensitivities in grillage system. The nonlinear constrained multi-objective optimization is a very important from the point of view of practical problem solving. Therefore, the real-coded genetic algorithm with multiple genetic operators is proposed to find the optimum grillage system without handling any of penalty functions. Direct strength calculation defined from the class rules of DNV was applied for structural design of grillage system. The hybrid method (real-coded genetic algorithm including the non-dominated sorting and sharing approaches) performs a marvelous explorability in finding a diverse set of solutions and in converging near the true Pareto-optimal set. The results obtained are very encouraging, since they show that we can produce an important portion of the Pareto-front at a very low computational time frame.

关键词： grillage system Pareto-sets real-coded genetic algorithm multi-objective optimization direct strength calculation DNV rules.

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Boosting‐Based optimization as a Generic Framework for Novelty and Fraud Detection in Complex Strategies

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AIP Conference Proceedings 2008年第1期1060卷 324-327页

作者： Valeriy V. Gavrishchaka Maria Kovbasinskaya Maria Monina aAlexandra Investment Management 767 Third Avenue 39 Floor New York NY 10017 bMoscow State University of Instrument Engineering and Computer Science Moscow Russian Federation

Novelty detection is a very desirable additional feature of any practical classification or forecasting system. Novelty and rare patterns detection is the main objective in such applications as fault/abnormality discovery in complex technical and biological systems, fraud detection and risk management in financial and insurance industry. Although many interdisciplinary approaches for rare event modeling and novelty detection have been proposed, significant data incompleteness due to the nature of the problem makes it difficult to find a universal solution. Even more challenging and much less formalized problem is novelty detection in complex strategies and models where practical performance criteria are usually multi‐objective and the best state‐of‐the‐art solution is often not known due to the complexity of the task and/or proprietary nature of the application area. For example, it is much more difficult to detect a series of small insider trading or other illegal transactions mixed with valid operations and distributed over long time period according to a well‐designed strategy than a single, large fraudulent transaction. Recently proposed boosting‐based optimization was shown to be an effective generic tool for the discovery of stable multi‐component strategies/models from the existing parsimonious base strategies/models in financial and other applications. Here we outline how the same framework can be used for novelty and fraud detection in complex strategies and models.

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A field-proven methodology for real-time drill bit condition assessment and drilling performance optimization

A field-proven methodology for real-time drill bit condition...

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SPE Russian Oil and Gas Technical Conference and Exhibition 2008

作者： Salakhov, Tagir R. Yamaliev, Vil U. Dubinsky, Vladimir Ufa State Petroleum Technological University Russia Baker Hughes United States

ISBN: (纸本)9781605607795

The primary objective of the proposed method is to evaluate the current conditions of the drilling system and suggest modifying values of main drilling control parameters to optimize the efficiency of the drilling in whole, while reducing the probability of premature wear of the drill bit. The fundamental theory behind the proposed approach is based on some elements of fractal analysis as well as artificial neural networks (NN). Many different complicated multi-parameter systems, including drilling systems, frequently discover scale invariance, or "fractality" of spatial-time properties. On this basis, some common engineering approaches to modeling and diagnostic methods have been developed and used. In our case, the "system" consists of the drilling components (e.g., surface equipment, drillstring, drill bit, mud, etc.), as well as the formation being drilled. Drilling control parameters include both the parameters adjustable in real-time, such as hook load, RPM, or mud flow rate, as well as those that can be modified with some delay (e.g., mud properties or configuration of the bottom-hole assembly). We consider specific examples of operational situations accompanying the drilling process, in which the fractal performances' application allows receiving important practical information during a standard operation, i.e., without carrying out a special controlled field experiment. We present some field examples that we used for gathering required data, training our model, and making an assessment of the current state of the system (specifically, the drill bit conditions) by using the proposed methodology. We also present the results of monitoring the system's response to specific adjustments of control parameters' values for these cases. We believe that the proposed methodology opens new opportunities for real-time drilling optimization that can be efficiently implemented within the scope of the existing drilling practice. Copyright 2008, Society of Petroleum Engineer

关键词： Fractals

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Digital PID controller design based on parametric optimization

Digital PID controller design based on parametric optimizati...

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IEEE Conference on Control Technology and Applications (CCTA)

作者： Adrian Gambier Automation Laboratory University of Heidelberg Mannheim Germany

PID control is probably the most applied control strategy around the world. There is also a huge amount of literature available about this control strategy. In the most common case, the controller is formulated in the continuous-time domain. If it is necessary to implement the controller as a computational algorithm, controllerpsilas equations are discretized. It is less frequent to find PID control laws, which are directly formulated as a discrete-time system. It is also possible, but unusual, to find design methods for digital PID controllers based on parametric optimization. Therefore, the objective of this paper is to revisit the digital PID/PI controller design based on parametric optimization including new advanced optimization methods as well as taking into consideration the new calculation machinery for several performance indices. Single as well as multi-objective optimization approaches are considered. Finally, available software and practical implementation aspects are highlighted.

关键词： Control systems USA Councils Conferences

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Towards a Suitable Reconciliation of the Findings in Collaborative Fuzzy Clustering

Towards a Suitable Reconciliation of the Findings in Collabo...

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International Conference on Intelligent Systems Design and Applications (ISDA)

作者： Rafael Falcón Benoît Depaire Koen Vanhoof Ajith Abraham Computer Science Department Central University of Las Villas Santa Clara Cuba Data Analysis and Modeling Hasselt University Diepenbeek Belgium Norwegian University of Science and Technology Trondheim Norway

This study is concerned with the application of multi-objective particle swarm optimization (MOPSO) approaches to the framework of collaborative fuzzy clustering. In particular, the emphasis lies in determining the collaboration matrix between the data repositories. By using fitness functions both at the level of data and information granules, we can provide a more effective way of reconciling the findings between the participating data sites. A practical application of the proposed methodology to marketing research is presented.

关键词： Application software International collaboration Fuzzy systems Particle swarm optimization optimization methods Clustering algorithms Intelligent systems System analysis and design Computer science Data analysis

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practical solutions for multi-objective optimization: An application to system reliability design problems

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2007年第3期92卷 314-322页

作者： Taboada, Heidi A. Baheranwala, Fatema Coit, David W. Wattanapongsakorn, Naruemon Rutgers State Univ Dept Ind & Syst Engn Piscataway NJ 08854 USA King Mongkuts Univ Technol Bangkok 10140 Thailand

For multiple-objective optimization problems, a common solution methodology is to determine a Pareto optimal set. Unfortunately, these sets are often large and can become difficult to comprehend and consider. Two methods are presented as practical approaches to reduce the size of the Pareto optimal set for multiple-objective system reliability design problems. The first method is a pseudo-ranking scheme that helps the decision maker select solutions that reflect his/her objective function priorities. In the second approach, we used data mining clustering techniques to group the data by using the k-means algorithm to find clusters of similar solutions. This provides the decision maker with just k general solutions to choose from. With this second method, from the clustered Pareto optimal set, we attempted to find solutions which are likely to be more relevant to the decision maker. These are solutions where a small improvement in one objective would lead to a large deterioration in at least one other objective. To demonstrate how these methods work, the well-known redundancy allocation problem was solved as a multiple objective problem by using the NSGA genetic algorithm to initially find the Pareto optimal solutions, and then, the two proposed methods are applied to prune the Pareto set. (c) 2006 Elsevier Ltd. All rights reserved.

关键词： system reliability multi-objective optimization pareto optimal set clustering analysis

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