The Problem of Invariance in Nonlinear Discrete-Time Dynamic Systems

Zhirabok, Alexey

doi:10.3390/sym12081241

Cited by 2 publications

(2 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is known for the discrete-time system [15] that to design the interval observer, the matrix F * should be stable and nonnegative; therefore, ICF ( 8) is preferable since it satisfies both conditions. A solution insensitive to the disturbance is based on Equation [29,30] (…”

Section: The Reduced Order Model Designmentioning

confidence: 99%

Interval Observers for Discrete-Time Linear Systems with Uncertainties

Sergiyenko

Zhirabok

Ibraheem³

et al. 2022

Symmetry

Self Cite

View full text Add to dashboard Cite

In this paper, we consider the problem involved when designing the interval observer for the system described by a linear discrete-time model under external disturbances and measurement noises. To solve this problem, we used the reduced order model of the initial system, which is insensitive or has minimal sensitivity to the disturbances. The relations involved in designing the interval observer, which has minimal dimensions and estimates the prescribed linear function of the original system state vector, were obtained. The theoretical results were illustrated by a practical example.

show abstract

Section: The Reduced Order Model Designmentioning

confidence: 99%

Interval Observers for Discrete-Time Linear Systems with Uncertainties

Sergiyenko

Zhirabok

Ibraheem³

et al. 2022

Symmetry

Self Cite

View full text Add to dashboard Cite

show abstract

“…In the field of geological survey, researchers use dynamic interpretation modeling technology for geological model construction framework [19,20]. is technology can respond to the construction process of geological layer modeling and fuse geological and geophysical data.…”

Section: Related Workmentioning

confidence: 99%

Discrete Dynamic Modeling and Change Trend Analysis of Regional Economy Based on Big Data

Chen

2021

Discrete Dynamics in Nature and Society

View full text Add to dashboard Cite

The driving force of high-quality development of regional economy is inseparable from the support of technology. With the support of big data, we need to solve this problem in order to solve the difficulty of large-scale experimental testing and accurately reflect the feasibility growth of data sample changes. This paper proposes a discrete dynamic modeling technology based on big data background to analyze the development and change of regional economy. The reliability AMSAA model is usually used for dynamic discrete modeling. It can be combined with the change data provided by big data to form a dynamic modeling method for reliability growth evaluation. Then, the Bayesian regression method is used to predict the change parameters of the model, and the spatial econometric method is used to analyze the regional economic change. The results show that compared with the traditional methods, the discrete dynamic modeling method is more accurate and can effectively solve the problem of reliable growth under the condition of big data. After introducing the spatial effect measurement model, it can also reflect the main factors of the growth and change of regional economic real output value. In addition to the development of high and new technology, terrain factors, investment, and government support have also had different effects. Therefore, according to the above results, it is proved that the discrete dynamic modeling technology can accurately obtain the experimental data and provide reliable technical support for dynamic data processing.

show abstract

The Problem of Invariance in Nonlinear Discrete-Time Dynamic Systems

Cited by 2 publications

References 23 publications

Interval Observers for Discrete-Time Linear Systems with Uncertainties

Interval Observers for Discrete-Time Linear Systems with Uncertainties

Discrete Dynamic Modeling and Change Trend Analysis of Regional Economy Based on Big Data

Contact Info

Product

Resources

About