Recent advances in modeling languages have made it feasible to formally specify and analyze the behavior of large system components. Synchronous data flow languages, such as Lustre, SCR, and RSML-e are well suited to ...
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Simulation modeling combined with decision control can offer important benefits for analysis, design, and operation of semiconductor supply-chain network systems. Detailed simulation of physical processes provides inf...
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Simulation modeling combined with decision control can offer important benefits for analysis, design, and operation of semiconductor supply-chain network systems. Detailed simulation of physical processes provides information for its controller to account for (expected) stochasticity present in the manufacturing processes. In turn, the controller can provide (near) optimal decisions for the operation of the processes and thus handle uncertainty in customer demands. In this paper, we describe an environment that synthesizes discrete-event system specification (DEVS) with model predictive control (MPC) paradigms using a knowledge interchange broker (KIB). This environment uses the KIB to compose discrete event simulation and model predictive control models. This approach to composability affords flexibility for studying semiconductor supply-chain manufacturing at varying levels of detail. We describe a hybrid DEVS/MPC environments via a knowledge interchange broker. We conclude with a comparison of this work with another that employs the Simulink/MATLAB environment.
The existing U.S. Paradigm of individual departmental laboratories is increasingly difficult to justify due to the interdisciplinary nature of modern controlengineering, the high cost and rapid obsolescence of techno...
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The existing U.S. Paradigm of individual departmental laboratories is increasingly difficult to justify due to the interdisciplinary nature of modern controlengineering, the high cost and rapid obsolescence of technology, and the demands on faculty time. The College of engineeringcontrol Systems Laboratory (COECSL) at the University of Illinois advocates a shift from departmental labs to college labs for pedagogical, as well as financial, reasons. This approach is proving to be an effective approach to undergraduate control systems education.
As the voltage and current waveforms are deformed due to transient during faults, their pattern changes according to the type of fault. The Artificial Neural Network (ANN) can then be used for fault detection due to i...
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ISBN:
(纸本)0780386108
As the voltage and current waveforms are deformed due to transient during faults, their pattern changes according to the type of fault. The Artificial Neural Network (ANN) can then be used for fault detection due to its distinguished behavior in pattern recognition. In order to minimize the structure and timing of the ANN, preprocessing of the voltage and current waveforms was done. The data delivered from a simulated power system using PSCAD (EMTP with cad system) was used for training and testing the ANN. An experimental setup, consists of a 3 phase power supply module and transmission line module, is utilized. A set of signal conditioning circuits is designed and implemented in order to transfer data to a PC which is used as an on-line relay for fault detection. This is done via a data acquisition card (CIO-DAS1602/12). The Matlab program captures and processes real data for training the ANN. Applying different types of faults for testing the system, right tripping action was taken and the type of fault was correctly identified. The suggested artificial neural network algorithm has been found simple and effective hence could be implemented in practical application.
Arithmetic operation's execution time in real-time system is bounded by deadlines. The method commonly used to meet these deadlines is by employing any suitable process-scheduling algorithm, which may contain a po...
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ISBN:
(纸本)0769522033
Arithmetic operation's execution time in real-time system is bounded by deadlines. The method commonly used to meet these deadlines is by employing any suitable process-scheduling algorithm, which may contain a potential weakness. If time needed to operate is longer than its deadline, then the result's quality will be poor. This is mainly caused by the algorithms of the arithmetic operations commonly used nowadays do not choose the most significant data to be processed first. This research tries to design new algorithm and its processing unit that works based on real-time principles, which starts its computation process from the highest valued digit and provides its intermediate-results that can be accessed anytime during the process. Designing tool used in this research is MAX+plus II Baseline 10.2 software. This research accomplishes in showing the performance of the new algorithm and its processing unit, which is better than the performance of the conventional algorithm.
Multi parameteric quadratic programming gives a full offline solution to a time varying quadratic programming (QP) problem arising during constrained predictive control. However, coding and implementation of this solu...
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Document Clustering is one of the popular techniques that can unveil inherent structure in the underlying data. Two successful models of unsupervised neural networks, Self-Organizing Map (SOM) and Adaptive Resonance T...
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K nearest-neighbor classification is an important method in pattern recognition. However, its computation complexity limits its real-time applications. The partial distance search is a solution to this problem. Althou...
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ISBN:
(纸本)0780386035
K nearest-neighbor classification is an important method in pattern recognition. However, its computation complexity limits its real-time applications. The partial distance search is a solution to this problem. Although it is not very effective, it can be combined with other algorithms to reduce the complexity. This paper proposes an indexing method that uses the variance vector of feature vectors of design set, to improve the efficiency of the partial distance search. The experimental results indicate the effectiveness of this indexing preprocessing.
A novel fast KNN classification algorithm is proposed for pattern recognition. The technique uses one important feature, mean of the vector, to reduce the search space in the wavelet domain. Since the proposed algorit...
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A novel fast KNN classification algorithm is proposed for pattern recognition. The technique uses one important feature, mean of the vector, to reduce the search space in the wavelet domain. Since the proposed algorithm rejects those vectors that are impossible to be the k closest vectors in the design set, it largely reduces the classification time and holds the classification performance as that of the original classification algorithm. The simulation on texture image classification confirms the efficiency of the proposed algorithm.
In this paper, a novel controller for parallel-connected online uninterruptible power supplies (UPS) without control interconnections based on the droop method is presented. The control approach consists in drop the f...
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In this paper, a novel controller for parallel-connected online uninterruptible power supplies (UPS) without control interconnections based on the droop method is presented. The control approach consists in drop the frequency of every module when its output power increases, resulting in an unavoidable nominal frequency deviation. Consequently, this method in its original form is only applicable to off-line or line-interactive UPS systems. As opposed to the conventional droop method, the proposed control scheme endows proper transient response, strictly frequency and phase synchronization with the ac mains, and excellent power sharing even for nonlinear loads. Hence, this controller is suitable for paralleled online UPS systems. Experimental results are obtained from two parallel-connected 1-kVA online UPS by using TMS320LF2407A DSP.
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