Synchronization for stochastic Lévy noise systems on a time-varying multi-weights network via delay intermittent control

2022 ◽  
Vol 108 ◽  
pp. 104594
Author(s):  
Hui Zhou ◽  
Qiguang Jiang ◽  
Wenxue Li
Keyword(s):  
Lévy Noise ◽  
Intermittent Control ◽  
Time Varying ◽  
Levy Noise

scholarly journals Stabilization for hybrid stochastic differential equations driven by Lévy noise via periodically intermittent control

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Yong Ren ◽  
Qi Zhang
Keyword(s):  
Continuous Time ◽  
Stochastic Systems ◽  
Main Idea ◽  
Lévy Noise ◽  
Intermittent Control ◽  
Controlled System ◽  
Hybrid Stochastic Systems ◽  
Levy Noise ◽  
Stability Results ◽  
Drift Coefficient

<p style='text-indent:20px;'>In this work, the issue of stabilization for a class of continuous-time hybrid stochastic systems with Lévy noise (HLSDEs, in short) is explored by using periodic intermittent control. As for the unstable HLSDEs, we design a periodic intermittent controller. The main idea is to compare the controlled system with a stabilized one with a periodic intermittent drift coefficient, which enables us to use the existing stability results on the HLSDEs. An illustrative example is proposed to show the feasibility of the obtained result.</p>

scholarly journals An Enhanced Intrinsic Time-Scale Decomposition Method Based on Adaptive Lévy Noise and Its Application in Bearing Fault Diagnosis

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 617
Author(s):  
Jianpeng Ma ◽  
Shi Zhuo ◽  
Chengwei Li ◽  
Liwei Zhan ◽  
Guangzhu Zhang
Keyword(s):  
Fault Diagnosis ◽  
Time Scale ◽  
Lévy Noise ◽  
Model Parameters ◽  
Rolling Bearings ◽  
Intrinsic Time ◽  
Time Scale Decomposition ◽  
Weak Fault ◽  
Levy Noise ◽  
The Impact

When early failures in rolling bearings occur, we need to be able to extract weak fault characteristic frequencies under the influence of strong noise and then perform fault diagnosis. Therefore, a new method is proposed: complete ensemble intrinsic time-scale decomposition with adaptive Lévy noise (CEITDALN). This method solves the problem of the traditional complete ensemble intrinsic time-scale decomposition with adaptive noise (CEITDAN) method not being able to filter nonwhite noise in measured vibration signal noise. Therefore, in the method proposed in this paper, a noise model in the form of parameter-adjusted noise is used to replace traditional white noise. We used an optimization algorithm to adaptively adjust the model parameters, reducing the impact of nonwhite noise on the feature frequency extraction. The experimental results for the simulation and vibration signals of rolling bearings showed that the CEITDALN method could extract weak fault features more effectively than traditional methods.

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