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Reweighted nuclear norm regularization: A SPARSEVA approach

IFAC-PapersOnLine 2015年第28期48卷 1172-1177页

作者： Ha, Huong Welsh, James S. Blomberg, Niclas Rojas, Cristian R. Wahlberg, Bo School of Electrical Engineering and Computer Science The University of Newcastle Technologiepark 913 B-9052 Gent Australia Department of Automatic Control and ACCESS School of Electrical Engineering KTH Royal Institute of Technology StockholmSE-100 44 Sweden

The aim of this paper is to develop a method to estimate high order FIR and ARX models using least squares with re-weighted nuclear norm regularization. Typically, the choice of the tuning parameter in the reweighting scheme is computationally expensive, hence we propose the use of the SPARSEVA (SPARSe Estimation based on a VAlidation criterion) framework to overcome this problem. Furthermore, we suggest the use of the prediction error criterion (PEC) to select the tuning parameter in the SPARSEVA algorithm. Numerical examples demonstrate the veracity of this method which has close ties with the traditional technique of cross validation, but using much less computations. © 2015

关键词： Parameter estimation Digital control systems Discrete time control systems Identification (control systems) Least squares approximations Numerical methods Discrete time systems Nuclear norm regularizations Nuclear norms regularization sparse estimate Sparse estimation Traditional techniques Validation criteria

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Optimal disturbance rejection via feedforward-PD for bilinear systems with external sinusoidal disturbances

Advances in Modelling and Analysis C

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Advances in Modelling and Analysis C 2016年第1期71卷 125-137页

作者： Liu, Guitao Fu, Mingyue Du, Houpeng School of Computer and Information Science Hubei Engineering University Xiaogan Hubei432000 China Department of Automatic Control Northwestern Polytechnical University Xi'an710072 China ZaoZhuang HongYi Automation Technology Co.LTD ZaoZhuang ShanDong277100 China

The optimal control problem is considered for bilinear systems affected by sinusoidal disturbances. A feedforward-PD optimal disturbance rejection control law based on output feedback of LQR is developed. By analysis the optimal disturbances rejection algorithms of bilinear systems based on time-domain state-space representation and the PD-control algorithms based on frequency-domain output feedback, the optimal PD tuning parameters are derived to achieve the purpose of optimal disturbances rejection. Finally, simulation results show that the algorithm is high in efficiency, easy to implement and well robust with respect to external sinusoidal disturbances.

关键词： Disturbance rejection

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Multi-flow rate control in delayed Wi-Fi offloading systems

Multi-flow rate control in delayed Wi-Fi offloading systems

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International Conference on Information Networking

作者： Yeongjin Kim Joohyun Lee Jaeseong Jeong Song Chong Korea Advanced Institute of Science and Technology Daejeon Daejeon KR Department of Electrical and Computer Engineering Ohio State University USA Automatic Control Department KTH Royal Institute of Technology Sweden School of Electrical Engineering KAIST South Korea

ISBN: (纸本)9781509017256

Explosive growth of mobile data traffic becomes an increasingly serious problem in cellular networks. Delayed Wi-Fi offloading is the concept to shift the delay-tolerant mobile traffic from cellular networks to Wi-Fi networks at the cost of additional delay. Existing studies mainly focused on a single-flow management or a multi-flow case without specified deadlines. In this paper, we address a multi-flow offloading problem in which a mobile user has multiple traffic flows whose loads and deadlines are different. More precisely, we formulate a multi-flow rate control based on a discrete and finite-horizon Markov decision problem. We develop a dynamic programming (DP)-based optimal rate control algorithm to maximize user satisfaction defined as offloading efficiency minus disutility due to deadline violations. Moreover, we propose a threshold-based rate control algorithm which requires low-complexity and low-memory but achieves high performance. Trace driven simulations based on measurements show that our proposed algorithms achieve high user satisfaction compared to existing algorithms.

关键词： IEEE 802.11 Standard Mobile communication Heuristic algorithms Delays Optimal scheduling Servers Mobile computing

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GPU Parallel Optimization of Hyperspectral Image Kernel Sparse Representation Classification Based on Spatial-Spectral Graph Regularization

GPU Parallel Optimization of Hyperspectral Image Kernel Spar...

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International Conference on Advanced Cloud and Big Data (CBD)

作者： Jida Zheng Zebin Wu Qicong Wang Jianjun Liu Zhihui Wei Wubin Wang Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Nanjing Jiangsu China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China North Automatic Control Technology Institute Taiyuan China

ISBN: (纸本)9781509036783

With the development of hyperspectral remote sensing information processing, hyperspectral image classification becomes a hot topic. The algorithm of kernel sparse representation classification based on spatial-spectral graph regularization and sparsity concentration index (SSGSCI-KSRC) gains a good result. Due to the big scale of hyperspectral image data, time-critical requirement in the practical application makes it impossible to use the original SSGSCI-KSRC algorithm. This paper proposes a parallelization method for SSGSCI-KSRC algorithm. The optimization method achieves the efficient calculation operations of hyperspectral image matrix data, coalesces memory accesses to reduce the time of transferring data to the GPU devices, and designs proper kernel functions in the classification algorithm. The experimental results demonstrate that the parallel SSGSCI-KSRC algorithm obtains a better result in terms of computational performance when the accuracy stays the same.

关键词： Classification algorithms Graphics processing units Kernel Hyperspectral imaging Algorithm design and analysis Training

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Decentralized MMSE attacks in electricity grids

Decentralized MMSE attacks in electricity grids

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IEEE/SP Workshop on Statistical Signal Processing (SSP)

作者： Iñaki Esnaola Samir M. Perlaza H. Vincent Poor Oliver Kosut Department of Electrical Engineering Princeton University Princeton NJ USA Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK Institut National de Recherche en Informatique et Automatique (INRIA) Lyon France School of Electrical Computer and Energy Engineering Arizona State University Tempe AZ USA

Decentralized data-injection attack construction with minimum mean-square-error state estimation is studied in a game-theoretic setting. Within this framework, the interaction between the network operator and the set of attackers, as well as the interactions among the attackers, are modeled by a game in normal form. A novel utility function that captures the trade-off between the maximum distortion that an attack can introduce and the probability of the attack being detected by the network operator is proposed. Under the assumption that the state variables can be modeled as a multivariate Gaussian random process, it is shown that the resulting game is a potential game. The cardinality of the corresponding set of Nash Equilibria (NEs) of the game is analyzed. It is shown that attackers can agree on a data-injection vector construction that achieves the best trade-off between distortion and detection probability by sharing only a limited number of bits offline. Interestingly, this vector construction is also shown to be an NE of the resulting game.

关键词： Games Distortion State estimation Conferences Covariance matrices

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Vehicle Logo Recognition by Spatial-SIFT Combined with Logistic Regression

Vehicle Logo Recognition by Spatial-SIFT Combined with Logis...

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International Conference on Information Fusion

作者： Ruilong Chen Matthew Hawes Lyudmila Mihaylova Jingjing Xiao Wei Liu Department of Automatic Control and Systems Engineering University of Sheffield S1 3JD UK School of Electronics Electrical and Computer Engineering University of Birmingham B15 2TT UK Department of Electronic and Electrical Engineering University of Sheffield S1 3JD UK

ISBN: (纸本)9781509020126

An efficient recognition framework requires both good feature representation and effective classification methods. This paper proposes such a framework based on a spatial Scale Invariant Feature Transform (SIFT) combined with a logistic regression classifier. The performance of the proposed framework is compared to that of state-of-the-art methods based on the Histogram of Orientation Gradients, SIFT features, Support Vector Machine and K-Nearest Neighbours classifiers. By testing with the largest vehicle logo data-set, it is shown that the proposed framework can achieve a classification accuracy of 99.93%, the best among all studied methods. Moreover, the proposed framework shows robustness when noise is added in both training and testing images.

关键词： Histograms Vehicles Logistics Dictionaries Support vector machines Robustness Training histograms vehicle Dictionaries as Topic Support Vector Network Logistics Functional training Logistic Regression Robustness Frameworks Power grids Training Classification Methods

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Self-triggered sampling for second-moment stability of state-feedback controlled SDE systems

Self-triggered sampling for second-moment stability of state...

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作者： Anderson, Ross P. Milutinović, Dejan Dimarogonas, Dimos V. Mechanical and Aerospace Engineering New York University Polytechnic School of Engineering United States Computer Engineering University of California Santa Cruz United States Automatic Control School of Electrical Engineering KTH Royal Institute of Technology Sweden

Event-triggered and self-triggered control, whereby the times for controller updates are computed from sampled data, have recently been shown to reduce the computational load or increase task periods for real-time embedded control systems. In this work, we propose a self-triggered scheme for nonlinear controlled stochastic differential equations with additive noise terms. We find that the family of trajectories generated by these processes demands a departure from the standard deterministic approach to event- and self-triggering, and, for that reason, we use the statistics of the sampled-data system to derive a self-triggering update condition that guarantees second-moment stability. We show that the length of the times between controller updates as computed from the proposed scheme is strictly positive and provide related examples. © 2015 Elsevier Ltd.

关键词： Stochastic systems

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Preface

SpringerBriefs in Applied Sciences and Technology

引用

SpringerBriefs in Applied Sciences and Technology 2016年 v页

作者： Sayed-Mouchaweh, Moamar Computer Science and Automatic Control Department High National Engineering School of Mines Douai France

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Preface

SpringerBriefs in Applied Sciences and Technology

引用

SpringerBriefs in Applied Sciences and Technology 2016年第9783319256658期 V-VI页

作者： Sayed-Mouchaweh, Moamar Computer Science and Automatic Control Department High National Engineering School of Mines Douai France

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control on a molecular scale: A perspective

Control on a molecular scale: A perspective

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American control Conference

作者： Rolf Findeisen Martha A. Grover Christian Wagner Michael Maiworm Ruslan Temirov F. Stefan Tautz Murti V. Salapaka Srinivasa Salapaka Richard D. Braatz S.O. Reza Moheimani Otto-von-Guericke-Universit?t Magdeburg Laboratory for Systems Theory and Automatic Control Germany School of Chemical & Biomolecular Engineering Georgia Institute of Technology USA Peter Gruenberg Institute (PGI-3) Juelich Research Center Germany Electrical and Computer Engineering Department University of Minnesota USA Massachusetts Institute of Technology USA Department of Mechanical Engineering The University of Texas at Dalla USA

ISBN: (纸本)9781467386838

Imaging and manipulating objects down to the molecular level plays a crucial role in many disciplines. It allows to unravel molecular phenomena, to form materials with new chemical and physical properties, or to build objects on an atomic scale. Science on the nanoscale is inherently interdisciplinary. It requires knowledge and insight into many fields, spanning from modeling, measuring, imaging, actuation to control. Often feedback control facilitates operation with molecular precision, despite the fact that many physical phenomena at the molecular level are still not well understood, and that stochastic and nonlinear effects are inherently present. This work provides an insight into some of the current control related research activities on a molecular scale. This is done considering examples from different fields: control related to scanning probe microscopy such as atomic force microscopy, controlled self assembly on a molecular scale, control aspects of molecular transport, and the use of control for manipulation of single molecules using macroscopic probe tips. The hope is that control related researchers, who are not experts in these fields, become aware of the opportunities present, which could also drive new theoretical developments.

关键词： Computational modeling Mathematical model Force Atomic force microscopy Numerical models Computational modeling Atomic Force Microscopy numerical models Mathematical Model Force Standing Orders Scale formation Insight Transport Process Physical Phenomena Scanning Probe Microscopy Hopefulness Research Activities chemical and physical properties feedback control

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