Structural Decomposition Approach for the Stability of Uncertain Dynamic Systems

1988 ◽  
Vol 55 (4) ◽  
pp. 992-994 ◽  
Author(s):  
Y. H. Chen ◽  
Chieh Hsu
Keyword(s):  
Dynamic Systems ◽  
A Priori ◽  
Parameter Variation ◽  
Stability Study ◽  
Fast Time ◽  
Time Varying ◽  
Decomposition Approach ◽  
New Approach ◽  
Uncertain Dynamic Systems ◽  
The Stability

The stability property for a class of dynamic systems with uncertain parameter variation is studied. The uncertainty can be fast time-varying and unpredictable. A new approach for stability study is proposed. The only required information on the uncertain variation is its possible bound as well as structure. That is, no a priori knowledge on the realization of the variation is needed.

A parametric family of Massey-type methods: inference, prediction, and sensitivity

2020 ◽  
Vol 16 (3) ◽  
pp. 255-269
Author(s):  
Enrico Bozzo ◽  
Paolo Vidoni ◽  
Massimo Franceschet
Keyword(s):  
Quantitative Analysis ◽  
Control Theory ◽  
Dynamic Systems ◽  
Parametric Family ◽  
Time Varying ◽  
Multi Agent ◽  
Key Features ◽  
The Stability ◽  
Agent Coordination ◽  
Time Aware

AbstractWe study the stability of a time-aware version of the popular Massey method, previously introduced by Franceschet, M., E. Bozzo, and P. Vidoni. 2017. “The Temporalized Massey’s Method.” Journal of Quantitative Analysis in Sports 13: 37–48, for rating teams in sport competitions. To this end, we embed the temporal Massey method in the theory of time-varying averaging algorithms, which are dynamic systems mainly used in control theory for multi-agent coordination. We also introduce a parametric family of Massey-type methods and show that the original and time-aware Massey versions are, in some sense, particular instances of it. Finally, we discuss the key features of this general family of rating procedures, focusing on inferential and predictive issues and on sensitivity to upsets and modifications of the schedule.

scholarly journals On Some Sufficiency-Type Global Stability Results for Time-Varying Dynamic Systems with State-Dependent Parameterizations

2019 ◽  
Vol 2019 ◽  
pp. 1-15
Author(s):  
M. De la Sen
Keyword(s):  
Global Stability ◽  
Dynamic Systems ◽  
Taylor Series Expansion ◽  
Time Varying ◽  
State Dependent ◽  
The Matrix ◽  
The Stability ◽  
Interval Type ◽  
Truncation Order ◽  
Stability Results

This paper formulates sufficiency-type global stability and asymptotic stability results for, in general, nonlinear time-varying dynamic systems with state-trajectory solution-dependent parameterizations. The stability proofs are based on obtaining sufficiency-type conditions which guarantee that either the norms of the solution trajectory or alternative interval-type integrals of the matrix of dynamics of the higher-order than linear terms do not grow faster than their available supremum on the preceding time intervals. Some extensions are also given based on the use of a truncated Taylor series expansion of chosen truncation order with multiargument integral remainder for the dynamics of the differential system.

scholarly journals Stability analysis for neural networks with discrete and leakage time-varying delay systems with delay-range-dependence and delay-derivative-dependence

2021 ◽  
Author(s):  
Pin-Lin Liu
Keyword(s):  
Neural Networks ◽  
Delay Systems ◽  
Linear Matrix ◽  
Time Varying ◽  
Decomposition Approach ◽  
Time Varying Delay ◽  
Systems Model ◽  
The Neural Networks ◽  
The Stability ◽  
Varying Delay

The paper deals with the stability problem of neural networks with discrete and leakage interval time-varying delays. Firstly, a novel Lyapunov-Krasovskii functional was constructed based on the neural networks leakage time-varying delay systems model. The delayed decomposition approach (DDA) and integral inequality techniques (IIA) were altogether employed, which can help to estimate the derivative of Lyapunov-Krasovskii functional and effectively extend the application area of the results. Secondly, by taking the lower and upper bounds of time-delays and their derivatives, a criterion on asymptotical was presented in terms of linear matrix inequality (LMI), which can be easily checked by resorting to LMI in Matlab Toolbox. Thirdly, the resulting criteria can be applied for the case when the delay derivative is lower and upper bounded, when the lower bound is unknown, and when no restrictions are cast upon the derivative characteristics. Finally, through numerical examples, the criteria will be compared with relative ones. The smaller delay upper bound was obtained by the criteria, which demonstrates that our stability criterion can reduce the conservatism more efficiently than those earlier ones.

scholarly journals Stability of conditionally invariant sets and controlled uncertain dynamic systems on time scales

1995 ◽  
Vol 1 (1) ◽  
pp. 1-10 ◽  
Author(s):  
V. Lakshmikantham ◽  
Z. Drici
Keyword(s):  
Time Scales ◽  
Dynamic Systems ◽  
Invariant Sets ◽  
Continuous Systems ◽  
Stability Properties ◽  
Closed Sets ◽  
Controlled Systems ◽  
Uncertain Dynamic Systems ◽  
Imperfect Knowledge ◽  
The Stability

A basic feedback control problem is that of obtaining some desired stability property from a system which contains uncertainties due to unknown inputs into the system. Despite such imperfect knowledge in the selected mathematical model, we often seek to devise controllers that will steer the system in a certain required fashion. Various classes of controllers whose design is based on the method of Lyapunov are known for both discrete [4], [10], [15], and continuous [3–9], [11] models described by difference and differential equations, respectively. Recently, a theory for what is known as dynamic systems on time scales has been built which incorporates both continuous and discrete times, namely, time as an arbitrary closed sets of reals, and allows us to handle both systems simultaneously [1], [2], [12], [13]. This theory permits one to get some insight into and better understanding of the subtle differences between discrete and continuous systems. We shall, in this paper, utilize the framework of the theory of dynamic systems on time scales to investigate the stability properties of conditionally invariant sets which are then applied to discuss controlled systems with uncertain elements. For the notion of conditionally invariant set and its stability properties, see [14]. Our results offer a new approach to the problem in question.

Robust Control of Generalized Dynamic Systems Without the Matching Conditions

1991 ◽  
Vol 113 (4) ◽  
pp. 582-589 ◽  
Author(s):  
Zhihua Qu ◽  
John Dorsey
Keyword(s):  
Robust Control ◽  
Dynamic Systems ◽  
Control Law ◽  
General Control ◽  
Matching Conditions ◽  
Uncertain Dynamic Systems ◽  
Special Cases ◽  
The Stability ◽  
Bounded Uncertainties

A general control law and a set of conditions are proposed to guarantee the stability of dynamic systems with bounded uncertainties. The results do not require the matching conditions on the uncertainties and subsume several existing results as special cases. Moreover, it is shown that there is at least one class of uncertain dynamic systems which can always be stabilized under the proposed control law no matter what the size and the structure of the input-unrelated uncertainties.

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