Analysis of the set of trajectories of nonlinear dynamics: Stability under interval initial conditions

2013 ◽  
Vol 49 (10) ◽  
pp. 1252-1260 ◽  
Author(s):  
A. A. Martynyuk ◽  
Yu. A. Martynyuk-Chernienko
2021 ◽  
Vol 16 (91) ◽  
pp. 125-143
Author(s):  
Aleksei A. Gavrishev ◽  

In this article, based on the mathematical, numerical and computer modeling carried out by the combined application of E&F Chaos, Past, Fractan, Visual Recurrence Analysis, Eviews Student Version Lite programs, some of the well-known 2D models of S-chaos are modeled, the data obtained are studied using nonlinear dynamics methods and the fact of their relation or non-relation to chaotic (quasi-chaotic) processes is established. As a result, it was found that the time diagrams obtained for the studied 2D models of S-chaos have a complex noise-like appearance and are continuous in the time domain. The resulting spectral diagrams have both a complex noise-like and regular appearance and are continuous in the spectral regions. The obtained values of BDS-statistics show that some of the time implementations can be attributed to chaotic (quasi-chaotic) processes. Also, the obtained values of BDS-statistics show that the studied 2D models of S-chaos have a property characteristic of classical chaotic (quasi-chaotic) processes: the slightest change in the initial conditions leads to the generation of a new set of signals. The obtained values of the lower bound of the KS-entropy show that the studied models also have the properties of chaotic (quasi-chaotic). Taking into account the conducted research and data from known works [1–5], it is possible to conclude that 2D models of S-chaos can relate to chaotic (quasi-chaotic) processes.


Author(s):  
Laura Ruzziconi ◽  
Abdallah H. Ramini ◽  
Mohammad I. Younis ◽  
Stefano Lenci

This study deals with an experimental and theoretical investigation of an electrically actuated micro-electro-mechanical system (MEMS). The experimental nonlinear dynamics are explored via frequency sweeps in a neighborhood of the first symmetric natural frequency, at increasing values of electrodynamic excitation. Both the non-resonant branch, the resonant one, the jump between them, and the presence of a range of inevitable escape (dynamic pull-in) are observed. To simulate the experimental behavior, a single degree-of-freedom spring mass model is derived, which is based on the information coming from the experimentation. Despite the apparent simplicity, the model is able to catch all the most relevant aspects of the device response. This occurs not only at low values of electrodynamic excitation, but also at higher ones. Nevertheless, the theoretical predictions are not completely fulfilled in some aspects. In particular, the range of existence of each attractor is smaller in practice than in the simulations. This is because, under realistic conditions, disturbances are inevitably encountered (e.g. discontinuous steps when performing the sweeping, approximations in the modeling, etc.) and give uncertainties to the operating initial conditions. A reliable prediction of the actual (and not only theoretical) response is essential in applications. To take disturbances into account, we develop a dynamical integrity analysis. Integrity profiles and integrity charts are performed. They are able to detect the parameter range where each branch can be reliably observed in practice and where, instead, becomes vulnerable. Moreover, depending on the magnitude of the expected disturbances, the integrity charts can serve as a design guideline, in order to effectively operate the device in safe condition, according to the desired outcome.


2002 ◽  
Vol 12 (12) ◽  
pp. 2967-2976 ◽  
Author(s):  
ZHENYA HE ◽  
WENJIANG PEI ◽  
LUXI YANG ◽  
STEPHEN S. HULL ◽  
JOHN Y. CHEUNG

The control of heart rate is primarily due to the function of the human autonomic nervous system. This process is deterministic but highly nonlinear. Due to the rapid response of the central nervous system, the actual heart rate is adjusted on a beat-to-beat basis. In this study, we propose the use of the cluster-weighted filtering (CWF) method to model the underlying deterministic mechanism of the variation of heart intervals. On a gross scale, a Gaussian network is used for function approximation to model the overall complex nonlinear dynamics of heart rate variability. At the same time, a noise reduction strategy based on Bayesian theory is used to eliminate the effects of noise on a finer scale. The algorithm iteratively models the nonlinear dynamics and reduces the noise components simultaneously. The proposed algorithm has been applied to 19 real data sets selected for analysis. The system dynamics was modeled from the experimental data sets. Based on the criterion for reconstruction used in this letter, the results suggested that the underlying deterministic dynamics could be reconstructed. A number of additional tests such as surrogate data and the largest Lyapunov exponent analyses were also carried out. Results confirmed that heart rate variability is a highly nonlinear process. It is further observed that the underlying deterministic mechanism of cardiac dynamics is highly sensitive to the initial conditions.


Author(s):  
Rafael H. Avanço ◽  
Hélio A. Navarro ◽  
Reyolando M. L. R. F. Brasil ◽  
José M. Balthazar

In this analysis, we consider the dynamics of a pendulum under vertical excitation of a crank-shaft-slider mechanism. The nonlinear model approaches that of a classical parametrically excited pendulum when the ratio of the length of the shaft to the radius of the crank is very large. Numerical techniques are employed to investigate the results for different parameters and initial conditions. Lyapunov exponents, bifurcation diagrams, time histories and phase portraits are presented to explore conditions when the pendulum performs or not full rotations. Of special interest are the resonance regions. Rotations together with oscillations and chaos were observed in some resonance zones.


2020 ◽  
Vol 19 (4) ◽  
pp. 683-706
Author(s):  
A.V. Leonov ◽  
A.Yu. Pronin

Subject. The article addresses the issue of adequate representation of economic dynamics. It considers the need to take into account internal nonlinear processes being an important factor and additional mechanism for managing the economic dynamics. Objectives. The purpose is to rationalize a transition to a new probabilistic mapping of economic dynamics based on modern methods of nonlinear dynamics, which enables to establish the relationship between internal nonlinear processes and macroeconomic indicators of the economic system. Methods. We employ a systems analysis of stages of State-run programs formation, a probabilistic approach to representing the economic dynamics on the basis of fundamental concepts and methods of nonlinear dynamics. Results. We analyzed the cycles of government program formation for developing the high-tech products, established the identity of the main stages of economic and nonlinear dynamics. We also designed a methodology for studying the economic dynamics, which rests on the use of nonlinear dynamics methods. Modeling the processes of economic dynamics made it possible to determine the causes of its sensitivity to initial conditions and exponential divergence of its trajectory at initial stages of government programs formation. The paper presents methods to choose the optimal model of economic dynamics when substantiating and drafting the said programs. Conclusions. The findings can be used to improve methodological tools for managing the creation of high-tech products when elaborating long-term technological programs, to reduce risk inherent in their implementation, to determine methods and ways for sustainable innovative and technological development of the country.


2013 ◽  
Vol 49 (1) ◽  
pp. 20-31 ◽  
Author(s):  
A. A. Martynyuk ◽  
Yu. A. Martynyuk-Chernienko

Target ◽  
2004 ◽  
Vol 16 (2) ◽  
pp. 201-226 ◽  
Author(s):  
Víctor M. Longa

The main concern of this article is to approach translation from the view of nonlinear dynamics. Thus, it makes use of theories related to such a type of dynamics (chaos theory and complexity science). This concern develops on two levels: firstly, the article argues that the abandonment of the traditional conception of translation and the raising of the current one actually agree with the evolution perceived in a great number of domains, such an evolution pointing to the rejection of deterministic positions. Secondly, it also defends the view that the translation process is entirely typical of the processes of nonlinear dynamics. Accordingly, key notions from nonlinear dynamics (such as sensitivity to initial conditions, phase transition, attractor or edge of chaos) are shown to apply to the nature of translation.


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