Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/614968
 Title: Optimal Communication Network-Based H_\infty Quantized Control With Packet Dropouts for a Class of Discrete-Time Neural Networks With Distributed Time Delay Authors: Qing-Long Han;Yurong Liu;Fuwen Yang subject: Discrete-time neural networks;distributed time delays;packet dropouts;quantized control.;H∞ control Year: 2016 Publisher: IEEE Abstract: This paper is concerned with optimal communication network-based H quantized control for a discrete-time neural network with distributed time delay. Control of the neural network (plant) is implemented via a communication network. Both quantization and communication network-induced data packet dropouts are considered simultaneously. It is assumed that the plant state signal is quantized by a logarithmic quantizer before transmission, and communication network-induced packet dropouts can be described by a Bernoulli distributed white sequence. A new approach is developed such that controller design can be reduced to the feasibility of linear matrix inequalities, and a desired optimal control gain can be derived in an explicit expression. It is worth pointing out that some new techniques based on a new sector-like expression of quantization errors, and the singular value decomposition of a matrix are developed and employed in the derivation of main results. An illustrative example is presented to show the effectiveness of the obtained results. URI: http://localhost/handle/Hannan/154246http://localhost/handle/Hannan/614968 ISSN: 2162-237X2162-2388 volume: 27 issue: 2 Appears in Collections: 2016

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