This paper investigates the implementation of a hybrid methodology, which combines fuzzy logic and neural networks, Fuzzy Cognitive Map (FCM), for the modeling of the supervisor of Large Scale Systems. The description...
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This paper investigates the implementation of a hybrid methodology, which combines fuzzy logic and neural networks, Fuzzy Cognitive Map (FCM), for the modeling of the supervisor of Large Scale Systems. The description and the construction of Fuzzy Cognitive Map will be extensively examined and it will be proposed a model for the supervisor. There is an oncoming need for more autonomous and intelligent systems, especially in Large Scale Systems and the application of Fuzzy Cognitive Map for the modeling of the Supervisor may contribute in the development of more autonomous systems.
It is shown that the stability of the stochastic approximation algorithm is implied by the asymptotic stability of the origin for an associated ODE. This in turn implies convergence of the algorithm. Several specific ...
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It is shown that the stability of the stochastic approximation algorithm is implied by the asymptotic stability of the origin for an associated ODE. This in turn implies convergence of the algorithm. Several specific classes of algorithms are considered as applications. It is found that the results provide: 1) a simpler derivation of known results for reinforcement learning algorithms; 2) a proof for the first time that a class of asynchronous stochastic approximation algorithms are convergent without using any a priori assumption of stability; and 3) a proof for the first time that asynchronous adaptive critic and Q-learning algorithms are convergent for the average cost optimal control problem.
A grey box model-based method for fault diagnosis is proposed in this paper. The method is based on a first principle model of the process unit: a heat exchanger, and on a grey box model of the faults: the deteriorati...
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A grey box model-based method for fault diagnosis is proposed in this paper. The method is based on a first principle model of the process unit: a heat exchanger, and on a grey box model of the faults: the deterioration of the heat transfer surface by aging and the leaking of the outer container. The deterioration of the heat transfer surface is due to material settling, and in old heat exchangers pieces of this material can break off and cause damage in the equipment. A recursive least squares estimator with forgetting factor is used to track both the heat transfer coefficients and the cold side volume. The heat transfer coefficients are estimated both from the hot and cold side equations. The settled material breakage fault is detected via detection of abrupt positive jumps in the estimated heat transfer coefficients using a detector based on a cumulative sum (CUSUM) test. The proposed method enables simultaneous detection of the two fault types considered. Fault localization along the equipment length is also possible when temperature measurements are available along the length.
作者:
Tzafestas, SGProkopiou, PAIntelligent
Robotics and Automation Laboratory Computer Science Division Department of Electrical and Computer Engineering National Technical University of Athens Zografou Campus 15773 Athens Greece
The response of a previously proposed teleoperator system, which was not based on the traditional notion of telepresence but on an original form of kinesthetic feedback, is tested under modeling errors of up to 50%. T...
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The response of a previously proposed teleoperator system, which was not based on the traditional notion of telepresence but on an original form of kinesthetic feedback, is tested under modeling errors of up to 50%. The original system is enhanced by replacing the previous controller of each robot with a sliding mode robust one. A two-stage approach is employed: a desired trajectory is first generated and then tracked by the controller. The difficulties incurred for the man/machine cooperation are discussed. This extension of the original teleoperator architecture is tested through simulations and compared with a twin system based on neural controllers, presented elsewhere. (C) 1997 Elsevier science Ltd.
Field-programmable gate arrays have the potential to provide reconfigurability in the presence of faults. In this paper, we have investigated the problem of partially reconfiguring FPGA mapped designs. We present a ma...
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Circuit partitioning is a very extensively studied problem. Our proposed methodology easily extends to multiple constraints that are very dominant in the design of large scale VLSI systems. In this paper we formulate ...
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Circuit partitioning is a very extensively studied problem. Our proposed methodology easily extends to multiple constraints that are very dominant in the design of large scale VLSI systems. In this paper we formulate the problem as a nonlinear program (NLP). The NLP is solved for the objective of minimum cutset size under the constraints of pins, area, and timing. We have tested the unified framework for area, timing, and pin constraints. The NLP is solved using the commercial LP/NLP solver MINOS. We have done extensive testing using large scale RT level benchmarks and have shown that our methods can be used for exploring the design space for obtaining constraint satisfying system designs. We also provide extensions for solving system design problems where a choice between multiple technologies, packaging components, performance, cost, yield, and more can be the constraints for design related decisions.
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 exa...
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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.
The paper exploits the combination of VRML (Virtual Reality Modeling Language) and Java for the construction of highly interactive animations, whose behaviour is defined in real time by a user's actions. The anima...
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The paper exploits the combination of VRML (Virtual Reality Modeling Language) and Java for the construction of highly interactive animations, whose behaviour is defined in real time by a user's actions. The animations are modeled in VRML, which allows the definition of a Java program to process and generate events that determine the behaviour of scene elements. An application for the generation of Java graphical interfaces was developed, aiming to establish the communication between the user and the VRML environment, sending parameters to the program that controls the animation.
We have developed a Web based application to accelerate the visualization of VRML scenes located in a remote server. This application enables the user to extract only the parts of a scene that are of actual interest. ...
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We have developed a Web based application to accelerate the visualization of VRML scenes located in a remote server. This application enables the user to extract only the parts of a scene that are of actual interest. The extracted parts represent one or more sub trees of the hierarchical structure of the VRML scene, and only these parts will be rendered and visualized in the local computer. By reducing the complexity (size) of the remote scene, less data are transmitted from the remote server and the rendering process becomes faster in the local computer. The application is written in Java and is executed as an applet embedded in an HTML page.
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)+…...
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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.
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