基于事件触发和量化的非线性系统稳定性研究

doi:10.16180/j.cnki.issn1007-7820.2020.03.011

Abstract

Abstract:

In this paper, based on the data sampling stability problem of nonlinear systems, a neural network controller based on event triggering mechanism and data quantization mechanism was designed. The sampler monitored the nonlinear system at any time, and the sampled signal was detected by the event trigger mechanism. After the threshold was satisfied, the quantizer was used to quantize the incoming controller, and the designed controller output the feedback and the nonlinear system. In order to reduce the conservativeness of the system, a novel piecewise Lyapunov-Krasovskii functional was selected. For the transmission time delay contained in the system, the time delay analysis method was used to transform the solving problem of the synchronous controller into the stability problem of the corresponding time-delay system. Combined with Jensen's inequality, the stability conditions of nonlinear systems were given. Finally, the effectiveness of the proposed method was verified by numerical simulation.

Key words: quantification, neural networks, data sampling, event trigger mechanism, nonlinear system, time-varying delay

CLC Number:

TP13

GUO Xin,GAO Yan,JIANG Lin,ZHANG Zhishu. Research on Stability of Nonlinear Systems Based on Event Triggering and Quantization[J].Electronic Science and Technology, 2020, 33(3): 56-61.

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References 18

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不同方法	采样间隔/s
文献[6]	0.066 2
文献[18]	0.109 3
本文	0.147 1

Research on Stability of Nonlinear Systems Based on Event Triggering and Quantization

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References 18

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