Nonlinear comparison systems and the stability of large-scale systems

1987 ◽  
Vol 23 (4) ◽  
pp. 378-382
Author(s):  
A. A. Martynyuk ◽  
Yu. N. Krapivnyi
Keyword(s):  
Large Scale ◽  
Large Scale Systems ◽  
Nonlinear Comparison ◽  
The Stability

Analysis of Stability for Generalized Discrete Large-Scale Systems

2013 ◽  
Vol 467 ◽  
pp. 627-632
Author(s):  
Chen Fang ◽  
Jiang Hong Shi ◽  
Shuang Yu ◽  
Jian Fang Mao
Keyword(s):  
Lyapunov Function ◽  
Large Scale ◽  
Lyapunov Equation ◽  
Large Scale Systems ◽  
Stability And Instability ◽  
Analysis Of Stability ◽  
The Stability

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.

Robust Decentralized Stabilization of Large-Scale Delay Systems Via Sliding Mode Control

1997 ◽  
Vol 119 (2) ◽  
pp. 307-312 ◽  
Author(s):  
Jun-Juh Yan ◽  
Jason Sheng-Hong Tsai ◽  
Fan-Chu Kung
Keyword(s):  
Sliding Mode Control ◽  
Large Scale ◽  
Sliding Mode ◽  
Delay Systems ◽  
Sliding Mode Controller ◽  
Stabilization Problem ◽  
Large Scale Systems ◽  
Decentralized Stabilization ◽  
Mode Control ◽  
The Stability

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.

Concept Of The Decomposition And Aggregation Method With Example: Part 1

1988 ◽  
pp. 27-40
Author(s):  
Dr. Zainol Anuar Mohd. Sharif ◽  
Ng Boon Choong
Keyword(s):  
Stability Analysis ◽  
Dynamic Systems ◽  
Basic Concept ◽  
Large Scale ◽  
Direct Method ◽  
Aggregation Method ◽  
Control Engineering ◽  
Large Scale Systems ◽  
Engineering Economics ◽  
The Stability

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.

An Approach, Via Entropy, to the Stability of Random Large-Scale Sampled-Data Systems Under Structural Perturbations

1982 ◽  
Vol 104 (1) ◽  
pp. 49-57 ◽  
Author(s):  
Guy Jumarie
Keyword(s):  
Stochastic Stability ◽  
Large Scale ◽  
Sufficient Conditions ◽  
Direct Application ◽  
Jacobian Determinant ◽  
Random Perturbations ◽  
Data Systems ◽  
Sampled Data ◽  
Large Scale Systems ◽  
The Stability

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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