139,585 research outputs found
A Parallel Divide-and-Conquer based Evolutionary Algorithm for Large-scale Optimization
Large-scale optimization problems that involve thousands of decision
variables have extensively arisen from various industrial areas. As a powerful
optimization tool for many real-world applications, evolutionary algorithms
(EAs) fail to solve the emerging large-scale problems both effectively and
efficiently. In this paper, we propose a novel Divide-and-Conquer (DC) based EA
that can not only produce high-quality solution by solving sub-problems
separately, but also highly utilizes the power of parallel computing by solving
the sub-problems simultaneously. Existing DC-based EAs that were deemed to
enjoy the same advantages of the proposed algorithm, are shown to be
practically incompatible with the parallel computing scheme, unless some
trade-offs are made by compromising the solution quality.Comment: 12 pages, 0 figure
A review on analysis and synthesis of nonlinear stochastic systems with randomly occurring incomplete information
Copyright q 2012 Hongli Dong et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.In the context of systems and control, incomplete information refers to a dynamical system in which knowledge about the system states is limited due to the difficulties in modeling complexity in a quantitative way. The well-known types of incomplete information include parameter uncertainties and norm-bounded nonlinearities. Recently, in response to the development of network technologies, the phenomenon of randomly occurring incomplete information has become more and more prevalent. Such a phenomenon typically appears in a networked environment. Examples include, but are not limited to, randomly occurring uncertainties, randomly occurring nonlinearities, randomly occurring saturation, randomly missing measurements and randomly occurring quantization. Randomly occurring incomplete information, if not properly handled, would seriously deteriorate the performance of a control system. In this paper, we aim to survey some recent advances on the analysis and synthesis problems for nonlinear stochastic systems with randomly occurring incomplete information. The developments of the filtering, control and fault detection problems are systematically reviewed. Latest results on analysis and synthesis of nonlinear stochastic systems are discussed in great detail. In addition, various distributed filtering technologies over sensor networks are highlighted. Finally, some concluding remarks are given and some possible future research directions are pointed out. © 2012 Hongli Dong et al.This work was supported in part by the National Natural Science Foundation of China under Grants 61273156, 61134009, 61273201, 61021002, and 61004067, the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant GR/S27658/01, the Royal Society of the UK, the National Science Foundation of the USA under Grant No. HRD-1137732, and the Alexander von Humboldt Foundation of German
A survey on modeling of microgrids - from fundamental physics to phasors and voltage sources
Microgrids have been identified as key components of modern electrical
systems to facilitate the integration of renewable distributed generation
units. Their analysis and controller design requires the development of
advanced (typically model-based) techniques naturally posing an interesting
challenge to the control community. Although there are widely accepted reduced
order models to describe the dynamic behavior of microgrids, they are typically
presented without details about the reduction procedure---hampering the
understanding of the physical phenomena behind them. Preceded by an
introduction to basic notions and definitions in power systems, the present
survey reviews key characteristics and main components of a microgrid. We
introduce the reader to the basic functionality of DC/AC inverters, as well as
to standard operating modes and control schemes of inverter-interfaced power
sources in microgrid applications. Based on this exposition and starting from
fundamental physics, we present detailed dynamical models of the main microgrid
components. Furthermore, we clearly state the underlying assumptions which lead
to the standard reduced model with inverters represented by controllable
voltage sources, as well as static network and load representations, hence,
providing a complete modular model derivation of a three-phase inverter-based
microgrid
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