The Stability of Large-Scale Systems in The Face of Small Perturbations

Author(s):  
M. Eremia ◽  
A. V. Gheorghe
2013 ◽  
Vol 467 ◽  
pp. 627-632
Author(s):  
Chen Fang ◽  
Jiang Hong Shi ◽  
Shuang Yu ◽  
Jian Fang Mao

Based on the condition that all independent subsystems of the generalized large-scale systems are regular and causal, this thesis studied both stability and instability of discrete linear generalized large-scale systems through Lyapunov equation and Lyapunov function, and proposed the criterion theorem for the stability or instability of discrete linear generalized large-scale systems.


1997 ◽  
Vol 119 (2) ◽  
pp. 307-312 ◽  
Author(s):  
Jun-Juh Yan ◽  
Jason Sheng-Hong Tsai ◽  
Fan-Chu Kung

The present paper is concerned with the decentralized stabilization problem of large-scale systems with delays in the intercon-nections using sliding mode control. A robust stability condition of the sliding mode and a robust decentralized sliding mode controller are newly derived for large-scale delay systems. Also a proportional-integral sliding mode is designed to make it easy to assure the stability of dynamics in the sliding mode.


1988 ◽  
pp. 27-40
Author(s):  
Dr. Zainol Anuar Mohd. Sharif ◽  
Ng Boon Choong

This paper describes the basic concept of the decomposition and aggregation method. It shows the feasibility of the method and its advantages when applied, particularly to large scale systems. This method is extensively used in solving problems related to control engineering, economics, optimization and stability. This paper also illustrates specifically the application of the method of decomposition and aggregation in the analysis of dynamic systems. It is divided into two important parts, namely; the decomposition part which involves breaking up a large system into subsystems and the aggregation part which is obtained through a reformulation of the Liapunov's second method (direct method). The relation between the decomposition and the aggregation methods is also shown. The procedure for checking the stability based on this concept is also outlined.For further illustration, an example of a dynamic system has been included. It shows how the system is decomposed and aggregated to suit the requirement for stability analysis.


1982 ◽  
Vol 104 (1) ◽  
pp. 49-57 ◽  
Author(s):  
Guy Jumarie

The concept of entropy in information theory is used to investigate the sensitivity and the stability of sampled-data systems in the presence of random perturbations. After a brief background on the definition, the practical meaning and the main properties of the entropy, its relations with asymptotic insensitiveness are exhibited and then some new results on the sensitivity and the stochastic stability of linear and nonlinear multivariable sampled data systems are derived. A new concept of stochastic conditional asymptotic stability is obtained which seems to be of direct application in the analysis of large-scale systems. Sufficient conditions for stability are stated. This approach provides a new look over stochastic stability. In addition, variable transformations act additively on entropy, via Jacobian determinant, and as a result the corresponding calculus is very simple.


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