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Extending CSP to detect motor imagery in a four-class BCI

Journal of Information and Computational Science 2012年第1期9卷 143-151页

作者： Fang, Yonghui Chen, Minyou Zheng, Xufei Harrison, R.F. State Key Laboratory of Power Transmission Equipment and System Security New Technology Chongqing University Chongqing 400044 China School of Electronic and Information Engineering Southwest University Chongqing 400715 China College of Computer Science Sichuan University Chengdu 610065 China Department of Automatic Control and Systems Engineering University of Sheffield United Kingdom

Brain computer Interface (BCI) provides a direct communication channel from brain to peripheral equipment. Common Spatial Patterns (CSP) is wildly used to extract features for electroencephalogram (EEG). However, basic CSP only suits two-class discrimination and is unable to solve multi-class discrimination problems. This paper proposes a modified CSP method termed Bisearch Common Spatial Patterns (BCSP) to solve a four-class BCI problem. In BCSP, the Fisher's Linear Discriminant Analysis (LDA) is used to discriminate among the four motor imagery tasks. The BCSP can effectively reduce the number of the basic CSP, and thus makes the overall classification procedure more efficient. The Graz BCI data set from the BCI 2008 competition be used to verify the effectiveness of the BCSP. Simulation results show that BCSP has better performance than other extension schemes. © 2012 Binary Information Press January 2012.

关键词： Brain computer interface

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Feature extraction of motor imagery in BCI with approximate entropy

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Journal of Computational Information systems 2012年第6期8卷 2485-2491页

作者： Fang, Yonghui Chen, Minyou Zheng, Xufei Harrison, Robert F State Key Laboratory of Power Transmission Equipment and System Security and New Technology Chongqing University Chongqing 400044 China School of Electronic and Information Engineering Southwest University Chongqing 400715 China College of Computer Science Sichuan University Chengdu 610065 China Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom

Approximate Entropy (ApEn) is a regularity statistic that quantifies the unpredictability of fluctuations in a time series and can classify complex systems. This study, ApEn is used to extract features from motor imagery Electroencephalogram (EEC) that containing two motor imagery tasks. This method is different from the traditional way to get the character from EEC. Appropriate parameters must been chosen for different dataset. Two datasets are used in this paper. One comes from BCI Competion2003, the other from the lab of Electromagnetic theory and artincal intelligence, Chongqing University. The results show that ApEn can extract different features in left-hand and right-hand motor imagery EEC efficiently. Comparison between ApEn and Fast Fourier Transform (FFT) shows that ApEn has good capability to the two imagery tasks Brain computer Interface. © 2012 Binary Information Press.

关键词： Electroencephalography

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A Recursive Local Linear Estimator for Identification of Nonlinear ARX systems *

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IFAC Proceedings Volumes 2012年第16期45卷 1517-1522页

作者： Wen-Xiao Zhao Wei Xing Zheng Er-Wei Bai Key Laboratory of Systems and Control Academy of Mathematics and Systems Science CAS Beijing P. R. China National Center for Mathematics and Interdisciplinary Sciences CAS Beijing P. R. China School of Computing Engineering and Mathematics University of Western Sydney Penrith NSW 2751 Australia Department of Electrical and Computer Engineering University of Iowa Iowa City IA 52242 USA

In this work, we propose a recursive local linear estimator (RLLE) for identification of nonlinear autoregressive systems with exogenous inputs, along with an analysis of its strong consistency and asymptotical mean s... 详细信息

关键词： Nonlinear ARX systems recursive identification local linear estimator almost sure convergence

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Robust Hybrid control for Ballistic Missile Longitudinal Autopilot

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Chinese Journal of Aeronautics 2011年第6期24卷 777-788页

作者： WAEL Mohsen Ahmeda WAEL Mohsen Ahmed QUAN Quan Department of Automatic Control School of Automation Science and Electrical Engineering Beihang University Beijing 100191 China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing 100191 China

This paper investigates the boost phase＇s longitudinal autopilot of a ballistic missile equipped with thrust vector control. The existing longitudinal autopilot employs time-invariant passive resistor-inductor-capacitor （RLC） network compensator as a control strategy, which does not take into account the time-varying missile dynamics. This may cause the closed-loop system instability in the presence of large disturbance and dynamics uncertainty. Therefore, the existing controller should be redesigned to achieve more stable vehicle response. In this paper, based on gain-scheduling adaptive control strategy, two different types of optimal controllers are proposed. The first controller is gain-scheduled optimal tuning-proportional-integral-derivative （PID） with actuator constraints, which supplies better response but requires a priori knowledge of the system dynamics. Moreover, the controller has oscillatory response in the presence of dynamic uncertainty. Taking this into account, gain-scheduled optimal linear quadratic （LQ） in conjunction with optimal tuning-compensator offers the greatest scope for controller improvement in the presence of dynamic uncertainty and large disturbance. The latter controller is tested through various scenarios for the validated nonlinear dynamic flight model of the real ballistic missile system with autopilot exposed to external disturbances.

关键词： ballistic missiles attitude control gain-scheduling optimal tuning-control LQ optimal regulators

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Towards an Ontology for Autonomous Robots

Towards an Ontology for Autonomous Robots

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2012 IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Liam Paull Gaetan Severac Guilherme V. Raffo Julian Mauricio Angel Harold Boley Phillip J Durst Wendell Gray Maki Habib Bao Nguyen S. Veera Ragavan Sajad Saeedi G. Ricardo Sanz Mae Seto Aleksandar Stefanovski Michael Trentini Howard Li COBRA Department of Electrical and Computer Engineering University of New Brunswick Fredericton Canada ONERA - University of Toulouse France Department of Automation and Systems Federal University of Santa Catarina Brazil Department of Computer Engineering Pontificia Universidad Javeriana Bogot Colombia National Research Council Canada US Army ERDC Vicksburg Ms Mechanical Engineering Department School of Sciences and Engineering The American University in Cairo New Cairo Egypt Defence Research and Development Canada - CORA Ottawa ON Canada Monash University Sunway Campus Systems Engineering and Automatic Control Autonomous Systems Laboratory research group Universidad Politcnica de Madrid Madrid Spain Defence Research and Development Canada - Atlantic NS Canada Department of Computer Science The George Washington University Defence R&D Canada - Suffield Medicine Hat AB Canada

ISBN: (纸本)9781467317375

The IEEE RAS Ontologies for Robotics and Automation Working Group is dedicated to developing a methodology for knowledge representation and reasoning in robotics and automation. As part of this working group, the Autonomous Robots sub-group is tasked with developing ontology modules for autonomous robots. This paper describes the work in progress on the development of ontologies for autonomous systems. For autonomous systems, the focus is on the cooperation, coordination, and communication of multiple unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), and autonomous underwater vehicles (AUVs). The ontologies serve as a framework for working out concepts of employment with multiple vehicles for a variety of operational scenarios with emphasis on collaborative and cooperative missions.

关键词： Ontologies Robot kinematics Sensors Planning Mobile robots Navigation

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A dual comparison principle for the analysis and design of discrete-time dynamical systems

A dual comparison principle for the analysis and design of d...

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作者： Bitsoris, George Athanasopoulos, Nikolaos Control Systems Laboratory Department of Electrical and Computer Engineering University of Patras 26500 Patras Greece

ISBN: (纸本)9783902661937

In this article, two new comparison principles for studying positive invariance and stability of linear and nonlinear discrete-time systems are presented. First, a general comparison principle enabling one to determine necessary and sufficient conditions of positive invariance of sets described by their "border surfaces" is developed. Then, a dual comparison principle describing the dynamics of the "vertices" of these sets is established. Both results can be used for the stability analysis and the control design of nonlinear systems. © 2011 IFAC.

关键词： Nonlinear systems

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Editorial-neural networks and learning systems come together

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IEEE Transactions on Neural Networks and Learning systems 2012年第1期23卷 1-6页

作者： Baesens, Bart Bouboulis, Pantelis Cruces, Sergio Domeniconi, Carlotta Ikeda, Shiro Li, Xuelong Melin, Patricia Rao, V. Sree Hari Schuller, Björn W. Shen, Yi Tang, Huajin Wang, Cong Yang, Jian Zhao, Dongbin Liu, Derong Catholic University of Leuven Belgium University of Athens Greece University of Seville Spain George Mason University United States Institute of Statistical Mathematics Japan University of London United Kingdom Tijuana Institute of Technology Mexico Jawaharlal Nehru Technological University India Technische Universität München Germany Huazhong University of Science and Technology China Institute for Infocomm Research Singapore Singapore South China University of Technology China Nanjing University of Science and Technology China Chinese Academy of Sciences China State Key Laboratory of Management Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Department of Electrical Computer Engineering University of Illinois Chicago IL 60607 United States

This issue marks the beginning of the IEEE Transactions on Neural Networks and Learning systems (TNNLS). By adding «Learning systems» to the title, we now state explicitly the scope of the TRANSACTIONS to include neural networks as well as related learning systems. This issue marks a new era in the history of our TRANSACTIONS. The TRANSACTIONS is now ready to face the challenges of the next 10-20 years. With the evolution of the fields of neural networks in particular and computational intelligence in general, the IEEE Transactions on Neural Networks and Learning systems will continue to grow and to succeed in this ever-changing world. Also included are a few comments about the review process of TNN manuscripts and the introduction of 14 new TNNLS Associate Editors. © 2012 IEEE.

关键词： Learning systems

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Integrated Approach to Hypersonic Vehicle Modeling

Integrated Approach to Hypersonic Vehicle Modeling

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Chinese control Conference

作者： Xiaofeng Su Yingmin Jia Junping Du Fashan Yu The Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Key Laboratory of Mathematics Informatics and Behavioral Semantics (LMIB) Ministry of Education SMSS Beihang University (BUAA) Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications School of Electrical Engineering and Automation Henan Polytechnic University

ISBN: (纸本)9781467325813

This paper is devoted to the modeling problem of hypersonic vehicle with significant couplings. An integrated approach is developed to analytically model the dynamics of hypersonic vehicle, in which the effects of variable mass, spherical rotating earth, and couplings among the sub-models are considered. Furthermore, a preliminary analysis is conducted using the general data of a hypersonic vehicle. The simulation results show that the maximum of the Coriolis force can reach values up to 7.02% of the vehicle weight, and that the thermal load determined by the nonuniform aerodynamic heating and the properties of the structure has a significant influence on the elastic deformation.

关键词： Hypersonic vehicle modeling Inertial dynamics Aerodynamics Elasticity Heating hypersonic vehicles Aerodynamics elasticity Coriolis force Vehicle weight Heating Couplings Thermal loading elastic deformation

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Power flow optimization using positive quadratic programming

Power flow optimization using positive quadratic programming

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作者： Lavei, Javad Rantzer, Anders Low, Stephen Department of Control and Dynamical Systems Caltech United States Automatic Control LTH Lund University Sweden Computer Science and Electrical Engineering Department Caltech United States

ISBN: (纸本)9783902661937

The problem to minimize power losses in an electrical network subject to voltage and power constraints is in general hard to solve. However, it has recently been discovered that semidefinite programming relaxations in many cases enable exact computation of the global optimum. Here we point out a fundamental reason for the successful relaxations, namely that the passive network components give rise to matrices with nonnegative offdiagonal entries. Recent progress on quadratic programming with Metzler matrix structure can therefore be applied. © 2011 IFAC.

关键词： Quadratic programming

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Stochastic H_2 Optimal control of Discrete-Time Markov Jump systems with Periodic Coefficients

Stochastic H_2 Optimal Control of Discrete-Time Markov Jump ...

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American control Conference

作者： Hongji Ma Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 Henan China

ISBN: (纸本)9781457710957

In this paper, the H_2 optimal state-feedback control problem is investigated for discrete-time Markov jump systems subject to periodic coefficients and multiplicative noise. First of all, an exhaustive analysis is pursued to set up an H_2 performance criterion (H_2 norm), which can be characterized by the periodic solutions of two generalized Lyapunov equations. Based on the obtained H_2 norm, the H_2 optimal state-feedback controller is designed in terms of the stabilizing solution of a discrete-time generalized Riccati equation with periodic coefficients. Moreover, this stabilizing solution can be computed efficiently by the available iterative algorithm.

关键词： Markov processes Noise Educational institutions Riccati equations Optimal control

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