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Entropy, Vol. 20, Pages 494: SIP-Based Single Neuron Stochastic Predictive Control for Non-Gaussian Networked Control Systems with Uncertain Metrology Delays

Entropy, Vol. 20, Pages 494: SIP-Based Single Neuron Stochastic Predictive Control for Non-Gaussian Networked Control Systems with Uncertain Metrology Delays

Entropy doi: 10.3390/e20070494

Authors: Xinying Xu Yalan Zhao Mifeng Ren Lan Cheng Mingyue Gong

In this paper, a novel data-driven single neuron predictive control strategy is proposed for non-Gaussian networked control systems with metrology delays in the information theory framework. Firstly, survival information potential (SIP), instead of minimum entropy, is used to formulate the performance index to characterize the randomness of the considered systems, which is calculated by oversampling method. Then the minimum values can be computed by optimizing the SIP-based performance index. Finally, the proposed strategy, minimum entropy method and mean square error (MSE) are applied to a networked motor control system, and results demonstrated the effectiveness of the proposed strategy.

Authors:   Xu, Xinying ; Zhao, Yalan ; Ren, Mifeng ; Cheng, Lan ; Gong, Mingyue
Journal:   Entropy
Volume:   20
edition:   7
Year:   2018
Pages:   494
DOI:   10.3390/e20070494
Publication date:   26-Jun-2018
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