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A NOVEL TECHNIQUE FOR CLASSIFICATION OF MYOELECTRIC SIGNALS FOR PROSTHESIS

IFAC Proceedings Volumes 2002年第1期35卷 447-451页

作者： B. Karlik M.O. Tokhi M. Alci Department of Computer Engineering University of Bahrain Bahrain Department of Automatic Control and Systems Engineering The University of Sheffield UK Department of Electrical and Electronics Engineering Ege University Izmir Turkey

This paper presents an investigation into classifying myoelectric signals using a new fuzzy clustering neural network architecture for control of multifunction prostheses. Moreover, a comparative study of the classification accuracy of myoelectric signals using multi-layer perceptron with back-propagation algorithm, and the new fuzzy clustering neural network (FCNN) is presented. The myoelectric signals considered are used to classify four upper-limb movements, which are elbow flexion, elbow extension, wrist pronation and wrist supination, grasp, and resting. The results suggest that FCNN can generalise better than the multi-layer perceptron without requiring extra computational effort. The proposed neural network algorithm allows the user to learn better and faster.

关键词： Fuzzy clustering neural network myoelectric signal pattern recognition

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Implementation of virtual factory using MMS companion standard

Implementation of virtual factory using MMS companion standa...

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IEEE International Workshop on Factory Communication systems (WFCS)

作者： Kwan-Joo Myoung Dong-Sung Kim Wook Hyun Kwon Engineering Research Center for Advanced Control Instrument Control Information Systems Laboratory School of Electrical Engineering and Computer Science Seoul National University Seoul South Korea

In this paper, a virtual factory using the manufacturing message specification (MMS) companion standard is implemented. The MMS companion standard (9506-3/spl sim/9506-7) and virtual machines are designed and implemented for robot, numerical controller (NC), programmable logic controller (PLC), and process control (PC). Finally, the MMS Internet monitoring system (MIMS) is developed for the testing system.

关键词： Production facilities Virtual manufacturing TCPIP Programmable control Virtual machining Condition monitoring Virtual machine monitors Manufacturing automation computer integrated manufacturing control systems

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Real-time reconfigurable control system design using on-line neural estimator

Real-time reconfigurable control system design using on-line...

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International Joint Conference on Neural Networks (IJCNN)

作者： Liang-Wei Ho G.G. Yen Intelligent Systems and Control Laboratory School of Electrical and Computer Engineering Oklahoma State University Stillwater OK USA

The growing demand in system reliability and survivability under failures has urged ever-increasing research effort on the development of fault diagnosis and accommodation. In this paper, the on-line fault tolerant control problem for dynamic systems under unanticipated failures is investigated from a realistic point of view without any specific assumption on type of system dynamical structure or failure scenarios. The sufficient condition for system on-line stability under catastrophic failures has been derived using the discrete-time Lyapunov stability theory. Based upon the existing control theory and the modern intelligent techniques, an on-line fault accommodation control strategy is proposed to deal with the desired trajectory-tracking problems for systems suffering from various unknown and unanticipated catastrophic failures. To investigate the feasibility of the developed technique for unanticipated fault accommodation in real hardware under the real-time environment, an on-line fault tolerant control test bed has been constructed to validate the proposed technology. Both on-line simulations and the real-time experiment show encouraging results and promising futures of on-line real-time fault tolerant control based solely upon insufficient information of the system dynamics and the failure modes.

关键词： Real time systems control systems Fault tolerant systems Reliability Fault diagnosis Sufficient conditions Stability Lyapunov method control theory Hardware

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Adaptive critic fault tolerant control using dual heuristic programming

Adaptive critic fault tolerant control using dual heuristic ...

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International Joint Conference on Neural Networks (IJCNN)

作者： G.G. Yen P.G. Lima Intelligent Systems and Control Laboratory School of Electrical and Computer Engineering Oklahoma State University Stillwater OK USA

In this paper a hierarchical architecture that combines a high degree of reconfigurability and long-term memory is proposed as a fault tolerant control algorithm for complex nonlinear systems. Dual heuristic programming (DHP) is used for adapting to faults as they occur for the first time in an effort to prevent the build up of a general failure and also as tuning device after switching to a known scenario. A dynamical database, initialized with as much information of the plant as available, oversees the DHP controller. The decisions of which environments to record, when to intervene and where to switch are autonomously taken based on specifically designed quality indexes. The results of the application of the complete algorithm to a proof-of-the-concept numerical example help to illustrate the fine interrelations between each of its subsystems.

关键词： Programmable control Adaptive control Fault tolerance control systems Nonlinear control systems Nonlinear systems Stability Databases Switches Algorithm design and analysis

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Hierarchical rank density genetic algorithm for radial-basis function neural network design

Hierarchical rank density genetic algorithm for radial-basis...

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Congress on Evolutionary Computation

作者： G.G. Yen Haiming Lu Intelligent Systems and Control Laboratory School of Electrical and Computer Engineering Oklahoma State University Stillwater OK USA

In this paper, we propose a genetic algorithm based design procedure for a radial-basis function neural network. A hierarchical rank density genetic algorithm (HRDGA) is used to evolve both the neural network's topology and parameters. In addition, the rank-density based fitness assignment technique is used to optimize the performance and topology of the evolved neural network to deal with the confliction between the training performance and network complexity. Instead of producing a single optimal network, HRDGA provides a set of near-optimal neural networks to the designers or the decision makers so that they can have more flexibility for the final decision-making based on their preferences. In terms of searching for a near-complete set of candidate networks with high performances, the networks designed by the proposed algorithm prove to be competitive, or even superior, to three selected traditional radial-basis function networks for predicting Mackey-Glass chaotic time series.

关键词： Genetic algorithms Neural networks Algorithm design and analysis Neurons Network topology Chaos Artificial neural networks Intelligent systems Intelligent control Intelligent networks

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Multiple-model reconfigurable control using adaptive critic

Multiple-model reconfigurable control using adaptive critic

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IEEE International Symposium on Intelligent control (ISIC)

作者： G.G. Yen P.G. Lima Intelligent Systems and Control Laboratory School of Electrical and Computer Engineering Oklahoma State University Stillwater OK USA

In this paper a hierarchical architecture that combines a high degree of reconfigurability and long-term memory is proposed as a fault tolerant control algorithm for complex nonlinear systems. Dual heuristic programming (DHP) is used for adapting to faults as they occur for the first time in an effort to prevent the build up of a general failure and also as tuning device after switching to a known scenario. A dynamical database, initialized with as much information of the plant as available, oversees the DHP controller. The decisions of which environments to record, when to intervene and where to switch are autonomously taken based on specifically designed quality indices. Results of the application of the complete algorithm to a proof-of-the-concept numerical example help to illustrate the fine interrelations between each of its subsystems.

关键词： Programmable control Adaptive control control systems Nonlinear control systems Nonlinear systems Stability Databases Switches Robust control Adaptive systems

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Dynamic database approach for fault tolerant control using dual heuristic programming

Dynamic database approach for fault tolerant control using d...

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American control Conference (ACC)

作者： G.G. Yen P.G. de Lima Intelligent Systems and Control Laboratory School of Electrical and Computer Engineering Oklahoma State University Stillwater OK USA

In this paper a hierarchical architecture that combines a high degree of reconfigurability and long-term memory is presented as a fault tolerant control algorithm for complex nonlinear systems. Dual heuristic programming (DHP) is used for adapting to faults as they happen for the first time in an effort to prevent the build up of a general failure and also as tuning device after switching to a known scenario. A dynamical database, initialized with as much information of the plant as available, oversees the DHP controller. The decisions of which environments to record, when to intervene and where to switch are autonomously made based on the specifically designed quality indexes. Results of the application of the complete algorithm to a proof-of-the-concept numerical example help to illustrate the fine interrelations between each of its subsystems.

关键词： Dynamic programming Databases Fault tolerance control systems Programmable control Adaptive control Nonlinear control systems Nonlinear systems Stability Switches

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On the local interpretation of Takagi-Sugeno fuzzy models from a dynamical systems view

On the local interpretation of Takagi-Sugeno fuzzy models fr...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Seok-beom Lee G.G. Yen Intelligent Systems and Control Laboratory School of Electrical and Computer Engineering Oklahoma State University Stillwater OK USA

Takagi-Sugeno (TS) fuzzy models have been the popular choice for multi-model based nonlinear system identification for controller design. However, the interpretation of the model from a dynamical systems point of view is still unclear. We investigate the interpretation of the TS fuzzy models in terms of local dynamics of nonlinear systems in state space. The investigation is based on the comparison between the constant-affine recursive i/o equation and constant-affine state space representations. We show that the true local dynamics is not identifiable by TS fuzzy models by analysis and example. For the identification of constant-affine state space models, a subspace identification algorithm is proposed to identify the true local dynamics with zero initial conditions.

关键词： Takagi-Sugeno model Fuzzy systems Least squares approximation Fuzzy control control system synthesis Nonlinear systems State-space methods Equations Function approximation Nonlinear control systems

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On the local interpretation of Takagi-Sugeno fuzzy models from a dynamical systems view

On the local interpretation of Takagi-Sugeno fuzzy models fr...

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American control Conference (ACC)

作者： Seok-beom Lee G.G. Yen Intelligent Systems and Control Laboratoly School of Electrical and Computer Engineering Oklahoma State University Stillwater OK USA

Takagi-Sugeno (TS) fuzzy models have been the popular choice for multi-model based nonlinear system identification for controller design. However, the interpretation of the model from a dynamical systems point of view is still unclear. In this paper, we investigate the interpretation of the TS fuzzy models in terms of local dynamics of nonlinear systems in state space. The investigation is based on the comparison between the constant-affine recursive i/o equation and constant-affine state space representations. We show that the true local dynamics is not identifiable by TS fuzzy models by analysis and example. For the identification of constant-affine state space models, a subspace identification algorithm is proposed to identify the true local dynamics with zero initial conditions.

关键词： Takagi-Sugeno model Fuzzy systems Least squares approximation control system synthesis Nonlinear systems State-space methods Equations Function approximation Fuzzy control Nonlinear control systems

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Facial feature extraction using genetic algorithm

Facial feature extraction using genetic algorithm

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Congress on Evolutionary Computation

作者： G.G. Yen N. Nithianandan Intelligent Systems and Control Laboratory School of Electrical and Computer Engineering Oklahoma State University Stillwater OK USA

An automatic facial feature extraction method is presented in this paper. The method is based on the edge density distribution of the image. In the preprocessing stage a face is approximated to an ellipse, and a genetic algorithm is applied to search for the best ellipse region match. In the feature extraction stage, the genetic algorithm is applied to extract the facial features, such as the eyes, nose and mouth, in the predefined sub regions. The simulation results validates that the proposed method is capable of automatically extracting features from various video images effectively under natural lighting environments and in the presence of certain amount of artificial noise and of multi-face oriented with angles.

关键词： Facial features Genetic algorithms Feature extraction Surveillance Data mining Data security Information security Biometrics Video coding Smart cards

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