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2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

作者： LING-YE NIE LEI LI JIA-MING CHEN Pattern Recognition and Intelligence System Institute of Automatic Control Engineering of Nanjing University of Posts and Telecomunications Nanjing 210003 China

A method of network component analysis(NCA) which separates blind sources using a priori information on the mixing matrix was put forward. Therefore blind source separation can be achieved without the assumption of statistical independence. Performance analysis is given comparing to FastICA and JADE through computer simulation. The superiority of NCA is validated without the assumption of statistical independence.

关键词： Network Component Analysis(NCA) Independent Component Analysis(ICA) Blind Source Separation(BSS)

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Annual business and news:: Beginning the 31st year of the Journal of Guidance, control, and Dynamics

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JOURNAL OF GUIDANCE control AND DYNAMICS 2008年第1期31卷 1-1页

作者： Schmidt, George T. Aeronautics and Astronautics Massachusetts Institute of Technology (MIT) AIAA Institute of Electrical and Electronics Engineers Russian Federation Academy of Navigation and Motion Control Department of Mechanical and Aerospace Engineering and Engineering Mechanics University of Missouri-Rolla(UMR) Lockheed Electronics Company Center for Space Research University of Texas Austin United States Wright Laboratory Eglin Air Force Base UMR AIAA Guidance Navigation and Control Technical Committee American Automatic Control Council Lockheed Martin Aeronautics Company Palmdale CA United States C4ISR and Unmanned Air Vehicle (UAV) Programs for Air Vehicle Sciences and Systems Accreditation Board Engineering and Technology Inc./Aeronautical National Technical Committee on Guidance Navigation and Control Department of Mechanical and Aerospace Engineering University at Buffalo State University of New York (SUNY) AIAA Technical Committee on GN and C Air Vehicles Directorate Air Force Research Laboratory (AFRL) Wright-Patterson Air Force Base Space Access and Hypersonic Vehicle Guidance and Control Group Control Science Center of Excellence AFRL AIAA Technical Committee on Guidance Navigation and Control Department of Mechanical and Aeronautical Engineering University of California (UC) Davis United States Boeing Company Modernized Flight Control System for the Apache Longbow AIAA Institute of Electrical and Electronics Engineers AHS Jet Propulsion Laboratory California Institute of Technology Boeing Company Flight Sciences and Advanced Design Group Guidance Navigation and Control (GN and C) Systems Engineer Distributed Space Systems NASA Goddard Space Flight Center (GSFC) AIAA GN and C Technical Committee Department of Aerospace Engineering and Engineering Mechanics University of Texas Austin United States Institute of Navigation American Astronautical Society AIAA Guidance Navigation (GN and C) and Control Technical Committee Department of Aerospace Engineering Iowa State University Iowa

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A Neural Networks based variable structure control scheme for induction motors

A Neural Networks based variable structure control scheme fo...

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11th IASTED International Conference on Intelligent systems and control, ISC 2008

作者： Barambones, Oscar Alkorta, Patxi Garrido, Aitor J. Garrido, Izaskun De La Sen, Manuel Maseda, Francisco J. Martija, Itziar Dept. of Automatic Control and System Engineering University of the Basque Country EUI Nieves cano 12 Vitoria Spain IIDP Facultad de Ciencias University of the Basque Country EUI Nieves cano 12 Vitoria Spain Dept. Mechanical Engineering University of the Basque Country EUI Nieves cano 12 Vitoria Spain

ISBN: (纸本)9780889867741

This paper presents a speed control of an induction motor. The design uses an feedforward Artificial Neural Network (ANN) to implement a rotor speed estimator, and a robust control strategy based on the sliding-mode. The proposed control scheme also make use of the field oriented control theory to simplify the proposed control design. The stability analysis of the presented control scheme is provided using the Lyapunov stability theory. Finally simulated results show that the presented controller with the proposed observer provides high-performance dynamic characteristics and that this scheme is robust with respect to plant parameter variations and external load disturbances.

关键词： Robust control

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control of parallel robots using passive sensor data

Control of parallel robots using passive sensor data

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2008 IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Asier Zubizarreta Itziar Cabanes Marga Marcos Charles Pinto Automatic Control and System Engineering Department University of Basque Country (UPV-EHU) Spain Mechanical Engineering Department University of Basque Country (UPV-EHU) Spain

ISBN: (纸本)9781424420575

A novel control architecture for parallel robots is introduced to fully exploit the advantages of these robots on high-speed and precision operation. A closed form of the dynamic model of parallel robots is difficult to obtain, due to the complex kinematic relations of these kind of mechanism. However, with the use of the extra data provided by sensors placed in strategic passive joints, kinematic and dynamic modelling can be simplified. The dynamic model can be used to implement advanced control techniques to improve the efficiency of parallel robots. In this paper, monoarticular and multiarticular control techniques are implemented on a 5R parallel robot, showing that the use of extra sensor data leads to a better and accurate control.

关键词： Joints Robots Mathematical model Sensors Robot sensing systems Kinematics Accuracy

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A framework for disturbance attenuation on SISO stable/unstable systems

A framework for disturbance attenuation on SISO stable/unsta...

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World Congress on Intelligent control and Automation (WCICA)

作者： R. Vilanova O. Arrieta P. Balaguer P. Ponsa Telecommunication and System Engineering Department School of Engineering ETSE Universitat Authnòma de Barcelona Barcelona Spain Department of Automatic Control Technical University of Catalonia Barcelona Spain

This paper presents a generalization of the internal model control (IMC) approach to feedforward control action generation. As it is well known, one of the distinctive features of the IMC formulation is the possibility to distinguish between the nominal and uncertain situation. However the consideration of the presence of uncertainty for the feedforward part of the controller is not as simple as it is for the feedback one. In this sense, what is proposed in this communication provides a more sistematic way of addressing a robust feedforward design. In addition, being one of the major drawbacks of the internal model control is to have to deal with stable systems, the generalization presented here allows for unstable plants as well as unstable disturbance models.

关键词： Feedforward neural networks Uncertainty Robustness Transfer functions Mathematical model Computational modeling Process control

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Real-Time Monitoring and Diagnosis Platform for a Machining Process

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IFAC Proceedings Volumes 2008年第2期41卷 10674-10679页

作者： E. Portillo M. Marcos I. Cabanes D. Orive J.A. Sánchez Department of Automatic Control and System Engineering Department of Mechanical Engineering E.T.S.I. de Bilbao (University of the Basque Country) Alameda Urquijo s/n 48013 Bilbao (SPAIN) (Tel: 0034 601 4049

This paper presents the design and development of a real-time monitoring and diagnosis system for diagnosing degraded cutting regimes in Wire Electrical Discharge Machining (WEDM). The detection in advance of the degradation of the cutting process is crucial since this can lead to the breakage of the cutting tool (the wire), reducing the process productivity and the required accuracy. This work presents the design and development of a real-time monitoring system that alerts of degraded operation. Unlike other works found in the literature review, which are focused on proprietary hardware, the present paper proposes a flexible real-time platform based on a commercial data acquisition board that can be easily configured for different purposes. It has been applied to develop a real-time monitoring and diagnosis system that uses virtual sensors to diagnose the process degradation. The results of this work show a satisfactory performance of the presented approach.

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ANN for Interpolating Instability Trends in WEDM

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IFAC Proceedings Volumes 2008年第2期41卷 2230-2235页

作者： E. Portillo M. Marcos I. Cabanes A. Zubizarreta J.A. Sánchez Department of Automatic Control and System Engineering Department of Mechanical Engineering E.T.S.I. de Bilbao (University of the Basque Country) Alameda Urquijo s/n 48013 Bilbao (SPAIN) (Tel: 0034 601 4049

In Wire Electrical Discharge Machining (WEDM) the breakage of the cutting tool (the wire) reduces the process performance and the required accuracy. Previous works of authors showed that the behavior of the basic signals of the process (current and voltage) can be employed to detect degraded situations that can lead to wire breakage. In particular, different types of degraded behaviors in two commonly used workpiece thicknesses (50 and 100 mm) were identified. In order to achieve this objective, a set of virtual sensors were defined and constructed from the basic signals of the process. Although the types of degraded behaviors were common for the studied workpiece thicknesses, the thresholds achieved by the virtual measurements depended on these. At the sight of this conclusion, the main goal of this work is to detect the process degradation in different workpiece thicknesses using one unique empirical model. Since Artificial Neural Networks are appropriated for processes of stochastic and nonlinear nature, its use is investigated here in order to interpolate the instability trends for different workpiece thicknesses. Firstly, a comparative study performed to select the most appropriated configuration of the neural network is summarized. Secondly, the strategy applied to detect degraded situations in different workpiece thicknesses is presented. The results of this work show a satisfactory performance of the presented approach.

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Optical and radio probing of lightning-associated phenomena in the atmosphere and ionosphere

Optical and radio probing of lightning-associated phenomena ...

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SICE Annual Conference

作者： T. Asano Y. Matsudo T. Suzuki Y. Hobara M. Hayakawa Department of Electronic Engineering University of Electro-Communications Chofu Tokyo Japan Air Force Defense Fuchu Tokyo Japan Department of Automatic Control and System Engineering Sheffield University UK

ISBN: (纸本)9784907764296

The monitoring and/or sounding of lightning discharges and their associated phenomena (mesospheric optical emissions etc.) has been performed by radio and optical measurements. We pay attention to the winter lightning in the Hokuriku area (Japan Sea side) of Japan, because it is extremely important to investigate whether lighting discharges in the Hokuriku area (whole spatial scale is relatively small in comparison with the conventional summer lightning in the US) could trigger the mesospheric optical emissions. The optical observation of those mesospheric emissions and the corresponding radio sounding by ELF and VHF radio waves of their parent lightning, have been reported. The observing systems are firstly presented, and our latest observational facts on the mesospheric emissions in the Hokuriku area, their parent lightning and some computer simulations on the sprite initiation, are presented.

关键词： Lightning Mesospheric emissions Optical measurement Radio measurement

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CARS setup for exhaust gas and combustion analysis

CARS setup for exhaust gas and combustion analysis

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IEEE Conference on Vehicle Power and Propulsion (VPPC)

作者： Hu Zhang Jing-min Dai Zhao Jin Chun-suo Xin Institute of Automatic Detecting and Process Control System (D&CS) Harbin Institute of Technology Harbin China Department of Electrical Engineering Harbin Institute of Technology Harbin China

ISBN: (纸本)9781424418480

Coherent anti-stokes Raman spectroscopy (CARS) is introduced, and several existing CARS methods are discussed and compared. Application in vehicle research is attempted through necessary modification on the basis of classical CARS theory. Classical theoretical spectrum calculation model is still suitable for the new situation. The design of CARS setup, which provides solutions for not only exhaust gas analysis but also engine combustion evaluation, is put forward. As the typical probe molecule, N 2 is modeled for combustion evaluation while CO 2 is emphasized on exhaust gas analysis. For multi-species analysis, several advanced CARS methods are introduced and expanded setup design using dual-pump CARS is shown. Elementary analysis has demonstrated that CARS has the capabilities of combustion evaluation and exhaust gas analysis. Temperature measurement accuracy can be plusmn10 K or higher and spatial resolution can be 1 cm or higher according to the instrument performance. Despite of some drawbacks the setup we developed can be useful for vehicle detection.

关键词： Combustion Vehicles Plasma measurements Raman scattering Plasma temperature Engines Instruments Frequency Spectroscopy Nonlinear optics

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Artificial Neural Networks for Detecting Instability Trends in Different Workpiece Thicknesses in a Machining Process

Artificial Neural Networks for Detecting Instability Trends ...

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2008 American control Conference (ACC), vol.3

作者： E. Portillo M. Marcos I. Cabanes A. Zubizarreta J.A. Sanchez Department of Automatic Control and System Engineering University of Basque Country (UPV-EHU) Bilbao Spain Department of Mechanical Engineering E.T.S.I. de Bilbao University of Basque Country (UPV-EHU) Bilbao Spain

This paper presents the use of Artificial Neural Networks to diagnose degraded behaviours in Wire Electrical Discharge Machining (WEDM). The detection in advance of the degradation of the cutting process is crucial since this can lead to the breakage of the cutting tool (the wire), reducing the process productivity and the required accuracy. Concerning this, previous investigations have identified different types of degraded behaviors in two commonly used workpiece thicknesses (50 and 100 mm). This goal was achieved by monitoring different functions of the characteristic variables of the discharges. However, the thresholds achieved by these functions depended on the workpiece thickness. Consequently, the main objective of this work is to detect the process degradation in different workpiece thicknesses using one unique empirical model Since Neural network techniques are appropriate for stochastic and nonlinear nature processes, its use is investigated here to cope with different workpiece thicknesses. The results of this work show a satisfactory performance of the presented approach.

关键词： Artificial neural networks Machining Degradation Wire Neural networks Electrodes Dielectrics Productivity Stochastic processes Ionization

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