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Markovian Delay Prediction-Based Control of Networked Systems | ||
| AUT Journal of Modeling and Simulation | ||
| مقاله 4، دوره 42، شماره 1، تیر 2010، صفحه 21-28 اصل مقاله (596.64 K) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22060/miscj.2010.185 | ||
| نویسندگان | ||
| Behrooz Rahmani؛ Amir H. D.Markaziii | ||
| چکیده | ||
| A new Markov-based method for real time prediction of network transmission time delays is introduced. The method considers a Multi-Layer Perceptron (MLP) neural model for the transmission network, where the number of neurons in the input layer is minimized so that the required calculations are reduced and the method can be implemented in the real-time. For this purpose, the Markov process order is estimated offline, using pr-recorded network time delay history. Unlike most of the previously existing methods, the proposed approach is both accurate and fast enough for a real time implementation. Using such a scheme for real-time estimation of the upcoming time delays, a variable state feedback gain control scheme is also proposed and applied to the predicted discretized model of the plant. The proposed approach is shown, through well-known benchmark problems, to be both accurate and fast enough for a real time implementation. | ||
| کلیدواژه‌ها | ||
| Neural Network؛ Delay Prediction؛ Entropy؛ Markov Order Estimation؛ Networked Control Systems (NCS)؛ Variable Controller Design | ||
| عنوان مقاله [English] | ||
| Markovian Delay Prediction-Based Control of Networked Systems | ||
| چکیده [English] | ||
| A new Markov-based method for real time prediction of network transmission time delays is introduced. The method considers a Multi-Layer Perceptron (MLP) neural model for the transmission network, where the number of neurons in the input layer is minimized so that the required calculations are reduced and the method can be implemented in the real-time. For this purpose, the Markov process order is estimated offline, using pr-recorded network time delay history. Unlike most of the previously existing methods, the proposed approach is both accurate and fast enough for a real time implementation. Using such a scheme for real-time estimation of the upcoming time delays, a variable state feedback gain control scheme is also proposed and applied to the predicted discretized model of the plant. The proposed approach is shown, through well-known benchmark problems, to be both accurate and fast enough for a real time implementation. | ||
| کلیدواژه‌ها [English] | ||
| Neural Network, Delay Prediction, Entropy, Markov Order Estimation, Networked Control Systems (NCS), Variable Controller Design | ||
| مراجع | ||
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