Time-Varying Modelling and Stability Analysis Method of Grid-Connected Inverter under the Long-Term Operation

Author(s):  
Yanbo Wang ◽  
Zhe Chen
2007 ◽  
Vol 17 (05) ◽  
pp. 407-417 ◽  
Author(s):  
QIANKUN SONG ◽  
JINDE CAO

In this paper, the impulsive Cohen-Grossberg neural network with unbounded discrete time-varying delays is considered. By using the analysis method and inequality technique, several sufficient conditions are obtained to ensure the global exponential stability of the addressed neural network. These results generalize the existing relevant stability results. Two examples with simulations are given to show the effectiveness of the obtained results.


2014 ◽  
Vol 898 ◽  
pp. 843-846
Author(s):  
Li Jun Wang

Generally, the obtained results on delayed systems can be classified into two types: delay-independent ones and delay-dependent ones. Delay-dependent stabilization problem for a class linear system with interval time-varying delay is studied. Early first proposed stability analysis method for systems with time-varying delay in a range, but the method therein still leaves much room for improvement. A sufficient condition in terms of linear matrix inequalities (LMIs) is achieved by constructing a novel Lyapunov-Krasovskii functional with the idea of partitioning the time delay, and then using free-weighting matrix approach and adopting inequalities, the interval delay is dealt with successfully. Compared with former stability analysis approaches, this approach can overcome the defect of finding a common positive definite matrix, and reduce conservative greatly. Finally, one simulation example is given to illustrate the effectiveness of the methods.


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