scholarly journals Flexible Nets: a modeling formalism for dynamic systems with uncertain parameters

2019 ◽  
Vol 29 (3) ◽  
pp. 367-392 ◽  
Author(s):  
Jorge Júlvez ◽  
Stephen G. Oliver
Keyword(s):  
Dynamic Systems ◽  
Uncertain Parameters ◽  
Modeling Formalism

scholarly journals FAULT DETECTION IN DISCRETE DYNAMIC SYSTEMS WITH UNCERTAINTY BASED ON INTERVAL OPTIMIZATION

2011 ◽  
Vol 16 (4) ◽  
pp. 549-557 ◽  
Author(s):  
Wei Li ◽  
Xiaoli Tian
Keyword(s):  
Fault Detection ◽  
Dynamic System ◽  
Dynamic Systems ◽  
Optimization Model ◽  
Uncertain Parameters ◽  
Interval Optimization ◽  
Numerical Examples ◽  
Discrete Dynamic ◽  
Discrete Dynamic System ◽  
Discrete Dynamic Systems

The imprecision and the uncertainty of many systems can be expressed with interval models. This paper presents a method for fault detection in uncertain discrete dynamic systems. First, the discrete dynamic system with uncertain parameters is formulated as an interval optimization model. In this model, we also assume that there are some errors of observation values of the inputs/outputs. Then, M. Hladík's newly proposed algorithm is exploited for this model. Some numerical examples are also included to illustrate the method efficiency.

scholarly journals A Bivariate Chebyshev Polynomials Method for Nonlinear Dynamic Systems With Interval Uncertainties

2021 ◽  
Author(s):  
Tonghui Wei ◽  
Feng Li ◽  
Guangwei Meng
Keyword(s):  
Dynamic Response ◽  
Dynamic Systems ◽  
Chebyshev Polynomials ◽  
Nonlinear Dynamic ◽  
Nonlinear Dynamic Systems ◽  
Uncertain Parameters ◽  
Entire Interval ◽  
Function Decomposition ◽  
Interval Uncertainties ◽  
Interval Functions

Abstract A bivariate Chebyshev polynomials approach is proposed to estimate the dynamic response bounds of nonlinear systems with interval uncertainties. The existing collocation method directly searches the maximum and minimum values of the surrogate model in the entire interval space by the scanning method (SM). The presence of too many uncertain parameters will lead to expansive computational cost. To overcome this shortcoming, the dynamic response is decomposed by a bivariate function decomposition (BFD), established based on high-order Taylor expansion, into the sum of multiple univariate and bivariate response functions. The above univariate and bivariate functions are fitted using Chebyshev polynomials, and polynomial coefficients are obtained through one-dimensional (1D) and two-dimensional (2D) interpolation points. Thus, the solution of the nonlinear dynamic systems with uncertain parameters can be transformed into that of univariate and bivariate Chebyshev interval functions. The extremum values of the low-dimensional Chebyshev interval functions can be found by SM, and then the bounds of dynamic response are acquired by interval arithmetic. Since SM searches for extreme values only in 1D and 2D uncertain domains, the amount of calculation is reduced compared to searching the whole uncertain space. The efficiency, practicability and effectiveness of the proposed interval uncertainty analysis method are proved by three dynamic examples.

scholarly journals Generalized Synchronization with Uncertain Parameters of Nonlinear Dynamic System via Adaptive Control

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Cheng-Hsiung Yang ◽  
Cheng-Lin Wu
Keyword(s):  
Adaptive Control ◽  
Dynamic Systems ◽  
Chaos Synchronization ◽  
Chaotic Dynamic ◽  
Nonlinear Dynamic System ◽  
Lyapunov Stability Theory ◽  
Adaptive Controller ◽  
Adaptive Synchronization ◽  
Uncertain Parameters ◽  
Control Scheme

An adaptive control scheme is developed to study the generalized adaptive chaos synchronization with uncertain chaotic parameters behavior between two identical chaotic dynamic systems. This generalized adaptive chaos synchronization controller is designed based on Lyapunov stability theory and an analytic expression of the adaptive controller with its update laws of uncertain chaotic parameters is shown. The generalized adaptive synchronization with uncertain parameters between two identical new Lorenz-Stenflo systems is taken as three examples to show the effectiveness of the proposed method. The numerical simulations are shown to verify the results.

Phase behavior of cationic and anionic surfactants at low concentrations

1992 ◽  
Vol 50 (1) ◽  
pp. 694-695
Author(s):  
E. Naranjo
Keyword(s):  
Phase Behavior ◽  
Structural Characterization ◽  
Dynamic Systems ◽  
Anionic Surfactants ◽  
Intermolecular Forces ◽  
Stable Form ◽  
Surfactant Mixtures ◽  
Low Concentrations ◽  
Cationic And Anionic Surfactants ◽  
General Method

Equilibrium vesicles, those which are the stable form of aggregation and form spontaneously on mixing surfactant with water, have never been demonstrated in single component bilayers and only rarely in lipid or surfactant mixtures. Designing a simple and general method for producing spontaneous and stable vesicles depends on a better understanding of the thermodynamics of aggregation, the interplay of intermolecular forces in surfactants, and an efficient way of doing structural characterization in dynamic systems.

Improving Feeding Outcomes in the NICU: Moving From Volume-Driven to Infant-Driven Feeding

2010 ◽  
Vol 19 (3) ◽  
pp. 68-74 ◽  
Author(s):  
Catherine S. Shaker
Keyword(s):  
Intensive Care Unit ◽  
Dynamic Systems ◽  
Neonatal Intensive Care ◽  
Well Being ◽  
Dynamic Systems Theory ◽  
Feeding Problems ◽  
Care Giving ◽  
Extremely Preterm ◽  
Extremely Preterm Infants

Current research on feeding outcomes after discharge from the neonatal intensive care unit (NICU) suggests a need to critically look at the early underpinnings of persistent feeding problems in extremely preterm infants. Concepts of dynamic systems theory and sensitive care-giving are used to describe the specialized needs of this fragile population related to the emergence of safe and successful feeding and swallowing. Focusing on the infant as a co-regulatory partner and embracing a framework of an infant-driven, versus volume-driven, feeding approach are highlighted as best supporting the preterm infant's developmental strivings and long-term well-being.

A Dynamic Systems Approach to Personality

2001 ◽  
Vol 6 (3) ◽  
pp. 172-176 ◽  
Author(s):  
Lawrence A. Pervin
Keyword(s):  
Dynamic Systems ◽  
Systems Approach ◽  
Biological Processes ◽  
Recent Advances ◽  
Dynamic View ◽  
The Future ◽  
History Of

David Magnusson has been the most articulate spokesperson for a holistic, systems approach to personality. This paper considers three concepts relevant to a dynamic systems approach to personality: dynamics, systems, and levels. Some of the history of a dynamic view is traced, leading to an emphasis on the need for stressing the interplay among goals. Concepts such as multidetermination, equipotentiality, and equifinality are shown to be important aspects of a systems approach. Finally, attention is drawn to the question of levels of description, analysis, and explanation in a theory of personality. The importance of the issue is emphasized in relation to recent advances in our understanding of biological processes. Integrating such advances into a theory of personality while avoiding the danger of reductionism is a challenge for the future.

Dynamic Systems for Everyone

1996 ◽  
Vol 41 (10) ◽  
pp. 1002-1003
Author(s):  
Esther Thelen
Keyword(s):  
Dynamic Systems
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