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IEEE International Conference on Automation science and Engineering (CASE)

作者： Biao Sun Peter B. Luh Qing-Shan Jia Ziyan Jiang Fulin Wang Chen Song Center of Intelligent and Networked Systems (CFINS) Tsinghua National Laboratory of Information Science and Technology Tsinghua University Beijing China Department of Electrical and Computer Engineering University of Connecticut Storrs CT USA Department of Building Science Tsinghua University Beijing China Safety and Control Systems China and the Tsinghu-UTC Research Institute of Integrated Building Energy United Technologies Research Center Inc. Beijing China

Improving the control of shading blinds, lights, natural ventilation, and HVAC systems while satisfying human comfort requirements can result in significant energy cost savings with time-of-day electricity pricing. Traditionally, the above-mentioned devices are controlled separately. In this paper, a novel formulation for the integrated control and the corresponding solution methodology are presented. The problem is to minimize daily energy costs of lights and HVAC systems while satisfying equipment capacities, system dynamics, and human comfort. The problem is complicated since 1) individual rooms are coupled as they compete for the HVAC with limited capacity and nonlinear characteristics, and 2) the problem is believed to be NP-hard in view that decision variables are all discrete. A solution methodology that combines Lagrangian relaxation and stochastic dynamic programming is developed within the surrogate optimization framework to obtain near-optimal strategies. These strategies are further refined to become novel control rules for easy practical implementation. Numerical simulation results show that both of the above strategies can effectively reduce the total energy cost, and that the integrated control works better than selected traditional control strategies.

关键词： Ventilation Humidity Equations Optimization Heating Humans

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A class of fractional dynamic systems with fuzzy order

A class of fractional dynamic systems with fuzzy order

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World Congress on intelligent Control and Automation (WCICA)

作者： HongGuang Sun XiaoNa Song YangQuan Chen Institute of Soft Matter Mechanics Department of Engineering Mechanics Hohai University HHU Nanjing Jiangsu China Center for Self-Organizing and Intelligent Systems (CSOIS) in the Department of Electrical and Computer Engineering Utah State University Logan UT USA School of Automation Nanjing University of Science and Technology of PLA Nanjing Jiangsu China

Differentiation and integration of non-integer order have drawn increasing attention in research community. Fractional order dynamic systems have been recognized as effective tools for characterizing the real-world phenomena around and inside us. From the notion of fuzzy logic, it is natural to quest the potential of fractional dynamic systems with fuzzy orders. In this paper, for the first time, we propose the basic framework of fractional order dynamic system with fuzzy order. This basic idea is to adopt fuzzy system to characterize the differential order in a class of variable-order or constant-order fractional dynamic systems. Examples are included to illustrate the operating process.

关键词： Output feedback Integrated circuit modeling Irrigation Mathematical model

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Stability analysis of a class of MIMO fuzzy control systems

Stability analysis of a class of MIMO fuzzy control systems

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Radu-Emil Precup Marius L. Tomescu Emil M. Petriu Stefan Preitl János Fodor Daniela Bărbulescu Department of Automation and Applied Informatics Polytechnic University of Timisoara Timisoara Romania “Politehnica” University of Timisoara Timisoara RO Romania Faculty of Computer Science Aurel Vlaicu University of Arad Arad Romania Faculty of Computer Science Complex Universitar Arad RO Romania University of Ottawa School of Information Technology and Engineering Ottawa ON Canada Óbuda University Institute of Intelligent Engineering Systems Budapest Hungary

This paper suggests a new stability analysis approach dedicated to a class of fuzzy control systems controlling multi input-multi output (MIMO) nonlinear processes by means of Takagi-Sugeno fuzzy logic controllers. The approach is based on LaSalle's global invariant set theorem, and an original stability theorem offers sufficient stability conditions. The applicability and efficiency of the theoretical results are illustrated by a MIMO case study dealing with the fuzzy control of a spherical three tank system.

关键词： Stability analysis Process control MIMO Fuzzy control Valves Numerical stability Lyapunov method

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Nonlinear IBVS Controller for the Flare Maneuver of Fixed-Wing Aircraft using Optical Flow

Nonlinear IBVS Controller for the Flare Maneuver of Fixed-Wi...

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2010 49th IEEE Conference on Decision and Control

作者： Pedro Serra Florent Le Bras Tarek Hamel Carlos Silvestre Rita Cunha Department of Electrical Engineering and Computer Science and Institute for Systems and Robotics Instituto Superior Tecnico 1049-001 Lisboa Portugal Laboratoire de Recherches Balistiques et Aerodynamiques (LRBA) of the French Delegation Generale pour 1Armement Vernon France I3S UNSA-CNRS Nice-Sophia Antipolis France

ISBN: (纸本)9781424477456

This paper describes a nonlinear Image-Based Visual Servo (IBVS) controller for the Flare phase of the landing maneuver of a fixed-wing aircraft in the presence of wind gust. Optic-Flow and 2D image features are exploited from the image of the runway to design a feedback controller for the automatic maneuver. The controller is divided into two parts. The first part guarantees the horizontal alignment with the center of the runway and uses the two lines delimiting the runway represented through a modification of the so-called Plucker coordinates. The second part takes advantage of the Optic-Flow measurements to ensure a smooth touchdown. Simulation results are presented to illustrate the performance of the control approach.

关键词： RUNWAY Fixed wing aircraft Optic Flow Wings feedback controller Controllers

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Novelty detection and 3D shape retrieval using superquadrics and multi-scale sampling for autonomous mobile robots

Novelty detection and 3D shape retrieval using superquadrics...

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IEEE International Conference on robotics and Automation (ICRA)

作者： P. Drews P. Núñez R. Rocha M. Campos J. Dias Dept. Computer Science Federal University of Minas Gerais Brazil ISIS Group Universidad de Málaga Spain Department Tecnología de los Computadores y las Comunicaciones Universidad de Extremadura Spain Institute of Systems and Robotics Department of Electrical and Computer Engineering University of Coimbra Portugal Dept. Tecnología de los Computadores y las Comunicaciones Universidad de Extremadura Spain Dept. Electrical and Computer Engineering University of Coimbra Portugal

There are several applications for which it is important to both detect and communicate changes in data models. For instance, in some mobile robotics applications (e.g. surveillance) a robot needs to detect significant changes in the environment (e.g. a layout change) which it may achieve by comparing current data provided by its sensors with previously acquired data (e.g. map) of the environment. This often constitutes an extremely challenging task due to the large amounts of data that must be compared in real-time. This paper proposes a framework to detect, and represent changes through a compact model. The main steps of the procedure are: multi-scale sampling to reduce the computation burden; change detection based on Gaussian mixture models; fitting superquadrics to detected changes; and refinement and optimization using the split and merge paradigm. Experimental results in various real and simulated scenarios demonstrate the approach's feasibility and robustness with large datasets.

关键词： Shape Sampling methods Mobile robots Robot sensing systems Navigation robotics and automation Information retrieval Data models Surveillance Simultaneous localization and mapping

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Fast weight calculation for kernel-based perceptron in two-class classification problems

Fast weight calculation for kernel-based perceptron in two-c...

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International Joint Conference on Neural Networks (IJCNN)

作者： M. Fernández-Delgado J. Ribeiro E. Cernadas S. Barro Intelligent Systems Group Spain School of Technology and Management Viana do Castelo Polytechnic Institute Viana do Castelo Portugal Department of Electronic and Computer Science University of Santiago de Compostela Santiago de Compostela Spain Universidade de Santiago de Compostela Santiago de Compostela Galicia ES

We propose a method, called Direct Kernel Perceptron (DKP), to directly calculate the weights of a single perceptron using a closed-form expression which does not require any training stage. The weigths minimize a performance measure which simultaneously takes into account the training error and the classification margin of the perceptron. The ability to learn non-linearly separable problems is provided by a kernel mapping between the input and the hidden space. Using Gaussian kernels, DKP achieves better results than the standard Support Vector Machine (SVM) and Linear Discriminant Analysis (LDA) for a wide variety of benchmark two-class data sets. The computational cost of DKP linearly increases with the dimension of the input space and it is much lower than the corresponding to SVM.

关键词： Support vector machines Training Kernel Accuracy Tuning Measurement uncertainty Spirals

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Probabilistic disc model based optimal node deployment scheme to target coverage in wireless sensor networks

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Tongxin Xuebao/Journal on Communications 2010年第9 A期31卷 1-8页

作者： He, Xin Gui, Xiao-Lin Department of Computer Science and Technology Xi'an Jiaotong University Xi'an 710049 China The Key Laboratory of Computer Network Xi'an 710049 China The Complex Intelligent Network Systems Institute of Henan University Kaifeng 475001 China

In wireless sensor networks, since the existing methods of dividing sensors based on the random deployment of nodes can not guarantee the optimal deployment to target coverage, a probabilistic disc model based optimal deterministic deployment scheme of sensor nodes was proposed. Firstly, probabilistic disc model was used to capture the stochastic nature of sensing. And, node sensing radius meeting to user needs was computed. Secondly, the candidate positions where nodes were placed to coverage target set were computed by using the concept of the most multi-overlapping domains of target point. Finally, known the candidate positions, by using simulated annealing genetic algorithm, the optimal positions and the least number of nodes to coverage target set were gained. Simulation results show that the nodes optimal deployment method is obtained based on user needs. The optimal allocation of resources is realized in wireless sensor networks.

关键词： Simulated annealing

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Evolutionary pressures for perceptual stability and self as guides to machine consciousness

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International Journal of Machine Consciousness 2009年第1期1卷 99-110页

作者： Franklin, Stan D'Mello, Sidney Baars, Bernard J. Ramamurthy, Uma Institute for Intelligent Systems Computer Science Department University of Memphis Memphis TN 38152 United States Neurosciences Institute San Diego CA United States

The currently leading cognitive theory of consciousness, Global Workspace Theory,1,2 postulates that the primary functions of consciousness include a global broadcast serving to recruit internal resources with which to deal with the current situation and to modulate several types of learning. In addition, conscious experiences present current conditions and problems to a "self" system, an executive interpreter that is identifiable with brain structures like the frontal lobes and precuneus.1 Be it human, animal or artificial, an autonomous agent3 is said to be functionally conscious if its control structure (mind) implements Global Workspace Theory and the LIDA Cognitive Cycle, which includes unconscious memory and control functions needed to integrate the conscious component of the system. We would therefore consider humans, many animals4 and even some virtual or robotic agents5,6 to be functionally conscious. Such entities may approach phenomenal consciousness, as found in human and other biological brains, as additional brain-like features are added. Here we argue that adding mechanisms to produce a stable, coherent perceptual field7 in a LIDA controlled mobile robot might provide a small but significant step toward phenomenal consciousness in machines.8 We also propose that implementing several of the various notions of self in such a LIDA controlled robot may well prove another step toward phenomenal consciousness in machines. © 2009 World Scientific Publishing Company.

关键词： Animals

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Consciousness is computational: The LIDA model of global workspace theory

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International Journal of Machine Consciousness 2009年第1期1卷 23-32页

作者： Baars, Bernard J. Franklin, Stan Neurosciences Institute San Diego CA 92121 United States Institute for Intelligent Systems Computer Science Department University of Memphis Memphis TN 38152 United States

We argue that the functions of consciousness are implemented in a bio-computational manner. That is to say, the conscious as well as the non-conscious aspects of human thinking, planning, and perception are produced by adaptive, biological algorithms. We propose that machine consciousness may be produced by similar adaptive algorithms running on the machine. Global Workspace Theory is currently the most empirically supported and widely discussed theory of consciousness. It provides a high-level description of such algorithms, based on a large body of psychological and brain evidence. LIDA provides an explicit implementation of much of GWT, which can be shown to perform human-like tasks, such as the interactive assignment of naval jobs to sailors. Here we provide brief descriptions of both GWT and LIDA in relation to the scientific evidence bearing on consciousness in the brain. A companion article explores how this approach could lead to machine consciousness. 1 We also discuss the important distinction between volition and consciously mediated action selection, and describe an operational definition of consciousness via verifiable reportability. These are issues that may well bear on the possibility of machine consciousness. © 2009 World Scientific Publishing Company.

关键词： Adaptive algorithms

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Incorporating prior knowledge into learning by dividing training data

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中国高等学校学术文摘·计算机科学 2009年第1期3卷 109-122页

作者： Baoliang LU Xiaolin WANG Masao UTIYAMA Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China MOE-Microsoft Key Lab for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University Shanghai 200240 China Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China National Institute of Information and Communications Technology (NICT) Kyoto 619-0288 Japan

In most large-scale real-world pattern classification problems, there is always some explicit information besides given training data, namely prior knowledge, with which the training data are organized. In this paper, we proposed a framework for incorporating this kind of prior knowledge into the training of min-max modular (M3) classifier to improve learning performance. In order to evaluate the proposed method, we perform experiments on a large-scale Japanese patent classification problem and consider two kinds of prior knowledge included in patent documents: patent's publishing date and the hierarchical structure of patent classification system. In the experiments, traditional support vector machine (SVM) and Ma-SVM without prior knowledge are adopted as baseline classifiers. Experimental results demonstrate that the proposed method is superior to the baseline classifiers in terms of training cost and generalization accuracy. Moreover, Ma-SVM with prior knowledge is found to be much more robust than traditional support vector machine to noisy dated patent samples, which is crucial for incremental learning.

关键词： prior knowledge patent classification support vector machine rain-max modular network task decomposition

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