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1997 IEEE International Conference on Neural Networks (ICNN 97)

作者： Tzafestas, SG Prokopiou, PA Tzafestas, CS Intelligent Robotics and Automation Laboratory Department of Electrical and Computer Engineering National Technical Unhersity of Athens Zografou 15773 Athens Greece Laboratoire de Robotique de Paris CNRS UPMC-UVSQ 78140 Velizy 10-12 AV. de 1' Europe France

ISBN: (纸本)0780341236

In this paper the control problem of telemanipulators is considered under the condition that they are subject to modeling and other uncertainties of considerable levels. The design is based on the S. Lee and H. S. Lee teleoperator control scheme, which is modified so as to be able to compensate the uncertainties, and is implemented using a partitioned multilayer perceptron neural network. Several subnetworks are used each one identifying a term of the manipulator's dynamic model. A new learning algorithm is proposed which distributes the learning error to each subnetwork and enables online training Several simulation results are provided which show the robustness ability by the partitioned neurocontroller, and compare it with the results obtained through sliding mode control.

关键词： Sliding mode control

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A Polynomial Function Discovery System — FFS

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International Journal on Artificial Intelligence Tools 1997年第1期6卷 1-13页

作者： Spyros Tzafestas Zhifang Ma Intelligent Robotics and Automation Laboratory Department of Electrical and Computer Engineering National Technical University of Athens Zografou 15773 Athens Greece On leave from the Department of Computer Science Jilin University Changchun P.R.China

This paper presents a function discovery system FFS that has two core parts: FFS-0-CORE and FFS-1-CORE. Both cores are with polynomial time complexity in discovering functions of either a•f(x)+b form or a 1 f 1 (x)+…+a n f n (x)+b form. FFS-0-CORE allows users to define their own models. FFS-1-CORE uses novel principles to increase information which helps the function discovery procedures. Three computational examples are included.

关键词： Formula discovery machine discovery machine learning artificial intelligence

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Introducing the theory of fuzzy cognitive maps in distributed systems

Introducing the theory of fuzzy cognitive maps in distribute...

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IEEE International Symposium on intelligent Control (ISIC)

作者： C.D. Stylios V.C. Georgopoulos P.P. Groumpos Laboratory for Automation and Robotics Department of Electrical and Computer Engineering University of Patras Rio Greece School of Electrical Engineering and Computer Science Ohio University Athens OH USA

This paper investigates a novel hybrid fuzzy neural system, fuzzy cognitive map (FCM), and its implementation in distributed systems and control problems. The description and the methodology of this system will be examined and then it will be shown the application of FCM in a process control problem, which will reveal the characteristics and qualities of FCM. There is an oncoming need for more autonomous and intelligent systems, which could be satisfied with the application of FCM in the field of systems and control.

关键词： Fuzzy cognitive maps Fuzzy systems Fuzzy logic intelligent systems robotics and automation Fuzzy control Control systems Control system synthesis Neural networks Humans

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SmartATMS : A Simulator For Air Traffic Management Systems

SmartATMS : A Simulator For Air Traffic Management Systems

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Simulation Winter Conference

作者： Tak-Kuen John Koo Yi Ma G.J. Pappas C. Tomlin Robotics and Intelligent Machines Laboratory Department of Electrical Engineering and Computer Science University of California Berkeley Berkeley CA USA

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Telemanipulator neurocontrol using multiple RBF networks

Telemanipulator neurocontrol using multiple RBF networks

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IEEE International Symposium on intelligent Control (ISIC)

作者： S.G. Tzafestas P.A. Prokopiou C.S. Tzafestas Intelligent Robotics and Automation Laboratory Department of Electrical and Computer Engineering National and Technical University of Athens Athens Greece Laboratoire de Robotique de Paris CNRS UPMC UVSQ France

This paper addresses the control problem of masterslave systems which involve severe modeling errors and other high-level uncertainties, using neural networks. The solution approach is based on a recent teleoperator control scheme of S. Lee and H.S. Lee (1993, 1994), which is suitably enhanced such that to become capable of compensating the uncertainties. The class of radial-basis functions (RBF) neural networks are employed in a multipartitioned neural network architecture, and a special learning scheme is adopted which distributes the learning error to each subnetwork and allows online learning. The effectiveness of the present RBF neurocontroller was investigated through extensive simulation and compared to that of MLP (multilayer perceptron) neurocontroller and a robust sliding-mode controller representative.

关键词： Radial basis function networks Robot kinematics Error correction Neural networks Teleoperators Master-slave Uncertainty Delay effects robotics and automation Neurocontrollers

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Growing region technique in the detection of autonomous structures within X-ray radiographs

Growing region technique in the detection of autonomous stru...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： S.N. Raptis S.G. Tzafestas S. Pavlopoulos D. Koutsouris S. Kollias Intelligent Robotics and Automation Laboratory National and Technical University of Athens Athens Greece Biomedical Engineering Laboratory National and Technical University of Athens Athens Greece Department of Electrical & Computer Engineering National and Technical University of Athens Athens Greece

Nodule identification is a major issue in chest radiography and cancer prevention and detection. The recognition of cancer nodule characteristics in chest radiographs is a key point to the detection procedure. The method described here is based on the extraction of the major geometrical as well as luminance characteristics that make nodule recognizable and easy to detect. The purpose of the proposed method is to detect within a given block of chest X-ray image any homogeneous and autonomous mass that might means the existence of a nodule or some structure within it. The idea of pixels of interest is introduced which makes the growing a finite steps procedure. The growing of the region around a given point is realized gradually in a finite number of iterations at each one of which a set of criteria is evaluated. These criteria are established in a prior training procedure.

关键词： X-ray detection X-ray detectors X-ray imaging Diagnostic radiography Pixel Laboratories Biomedical engineering Cancer detection Character recognition Shape

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The active kinematic histogram method for path planning of non-point, non-holonomically constrainted mobile robots

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Advanced robotics 1997年第4期12卷 373-395页

作者： Katevas, Nikos I. Tzafestas, Spyros G. Zenon SA - Industrial Automation Athens 15344 Kanari 5 Greece Intelligent Robotics and Automation Laboratory Department of Electrical and Computer Engineering National Technical University of Athens Athens 15773 Zografou Campus Greece

The paper presents a novel path planning method for non-point, non-holonomically constrainted mobile robots. The proposed method, named the Active Kinematic Histogram (AKH) method, is a potential field path-planning method based on the Vector Field Histogram (VFH) method introducedby J. Borenstein and Y. Koren. The method relies on one-dimensional environment representations named AKHs, derived from the available information on the obstacle space and the robot itself. The AKHs provide the information abstraction required for fast, collision-free and kinematically feasiblepath planning for non-point, non-holonomically constrainted mobile robots. The method constructs two AKH structures incorporating the information stored in occupancy grid environment representations as well as the exact robot's size, shape and kinematic features. The method applies simpleand fast procedures, e.g. histogram shifting, in order to determine kinematic feasibility and the result of the robot's steering limits. Being a potential field method, the AKH method uses adaptive thresholding procedures to reduce the inherited drawback of the local minima traps ***, the method proposes specific updating and coding procedures for the environmental information and introduces the Ageing function to insert time parameterization in the path-planning results. Also, the so-called bicycle kinematic model is presented in order to describe the kinematicfamily of mobile robots suitable for applying the AKH method. The method integrates a velocity control procedure which is also based on information provided by the active kinematic histograms. The method produced smooth, collision-free paths in a variety of experimental configurations. Simulationand experimental results are presented. © VSP and robotics Society of Japan 1997.

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Neural Fault Detection and Accommodation for Interconnected Power Systems

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IFAC Proceedings Volumes 1997年第18期30卷 943-947页

作者： Spyros Tzafestas Yiannis Anthopoulos Efthimios Kyriannakis Intelligent Robotics and Automation Laboratory Department of Electrical and Computer Engineering National Technical University of Athens Zographou 15773 Athens Greece. Tel: +30-1-7722489 +30-1-772-1527 Fax: +30-1-7722490 +30-1-7722459

Due to increasing safety and reliability demands fault detection and accommodation is a key issue in the design of industrial control systems. This paper presents a neural network based method for fault detection and accommodation, appropriate for interconnected power systems. The simulation results show that the method is very promising.

关键词： fault detection neural networks interconnected systems

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Robust telemanipulator control using a partitioned neural network architecture

Robust telemanipulator control using a partitioned neural ne...

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International Conference on Neural Networks

作者： S.G. Tzafestas P.A. Prokopiou C.S. Tzafestas Intelligent Robotics and Automation Laboratory Department of Computer Engineering National and Technical University of Athens Athens Greece Laboratoire de Robotique de Paris CNRS UPMC UVSQ Velizy France

In this paper the control problem of telemanipulators is considered under the condition that they are subject to modeling and other uncertainties of considerable levels. The design is based on the S. Lee and H.S. Lee teleoperator control scheme (1993, 1994), which is modified so as to be able to compensate the uncertainties, and is implemented using a partitioned multilayer perceptron neural network. Several subnetworks are used each one identifying a term of the manipulator's dynamic model. A new learning algorithm is proposed which distributes the learning error to each subnetwork and enables online training. Several simulation results are provided, which show the robustness ability by the partitioned neurocontroller, and compare it with the results obtained through sliding mode control.

关键词： Robust control Neural networks Uncertainty Teleoperators Multilayer perceptrons Multi-layer neural network Manipulator dynamics Partitioning algorithms Neurocontrollers Sliding mode control

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Synthesized passive feedback control of sensor-rich structures

Synthesized passive feedback control of sensor-rich structur...

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American Control Conference (ACC)

作者： P. Akella J.T. Wen Control Laboratory for Mechanical Structures (CLaMS) Center for Advanced Technology in Automation Robotics & Manufacturing Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY USA

The passivity property of dissipative mechanical structures has long been exploited in designing passive controllers that provide robust stability even in the presence of unmodeled dynamics of the system. For an input/output map of a flexible structure to be passive, collocation of the actuators and sensors is required and also the sensors should measure the velocity of the system. The so-called smart structures frequently have more sensors than actuators. Therefore, the passive controller can at best utilize only a subset of the sensors. In this paper we consider the design of a squaring down matrix which would render a system passive subject to some additional performance considerations. The problem of obtaining the synthesized passive output is cast as a set of linear matrix inequalities (LMIs) which can be efficiently solved by the LMI Toolbox in Matlab. We apply this procedure with the assumption that the sensors provide both displacement and velocity information which is generally not true. We show that the passive controllers can be implemented without the use of velocity information. By using synthesized passive outputs in addition to naturally occurring passive outputs, we obtain better system performance. We present experimental results involving a single flexible beam with torque input and hub angular position and strain gage outputs.

关键词： Feedback control intelligent sensors Control system synthesis Mechanical sensors Sensor systems Linear matrix inequalities Mechanical factors Control systems Robust stability Flexible structures

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