The Stochastic Response of a Class of Impact Systems Calculated by a New Strategy Based on Generalized Cell Mapping Method

2018 ◽  
Vol 85 (5) ◽  
Author(s):  
Liang Wang ◽  
Shichao Ma ◽  
Chunyan Sun ◽  
Wantao Jia ◽  
Wei Xu
Keyword(s):  
Transition Probability ◽  
Transition Probability Matrix ◽  
Mapping Method ◽  
Cell Mapping ◽  
Stochastic Response ◽  
Generalized Cell Mapping ◽  
Significant Difference ◽  
New Strategy ◽  
Almost All ◽  
The Impact

In this paper, a new strategy based on generalized cell mapping (GCM) method will be introduced to investigate the stochastic response of a class of impact systems. Significant difference of the proposed procedure lies in the choice of a novel impact-to-impact mapping, which is built to calculate the one-step transition probability matrix, and then, the probability density functions (PDFs) of the stochastic response can be obtained. The present strategy retains the characteristics of the impact systems, and is applicable to almost all types of impact systems indiscriminately. Further discussion proves that our strategy is reliable for different white noise excitations. Numerical simulations verify the efficiency and accuracy of the suggested strategy.

On the Data-Driven Generalized Cell Mapping Method

2019 ◽  
Vol 29 (14) ◽  
pp. 1950204 ◽  
Author(s):  
Zigang Li ◽  
Jun Jiang ◽  
Ling Hong ◽  
Jian-Qiao Sun
Keyword(s):  
Global Analysis ◽  
Transition Probability ◽  
Transition Probability Matrix ◽  
Mapping Method ◽  
Data Driven ◽  
Cell Mapping ◽  
Time Step ◽  
Generalized Cell Mapping ◽  
Step Transition ◽  
The One

Global analysis is often necessary for exploiting various applications or understanding the mechanisms of many dynamical phenomena in engineering practice where the underlying system model is too complex to analyze or even unavailable. Without a mathematical model, however, it is very difficult to apply cell mapping for global analysis. This paper for the first time proposes a data-driven generalized cell mapping to investigate the global properties of nonlinear systems from a sequence of measurement data, without prior knowledge of the underlying system. The proposed method includes the estimation of the state dimension of the system and time step for creating a mapping from the data. With the knowledge of the estimated state dimension and proper mapping time step, the one-step transition probability matrix can be computed from a statistical approach. The global properties of the underlying system can be uncovered with the one-step transition probability matrix. Three examples from applications are presented to illustrate a quality global analysis with the proposed data-driven generalized cell mapping method.

A Statistical Study of Generalized Cell Mapping

1988 ◽  
Vol 55 (3) ◽  
pp. 694-701 ◽  
Author(s):  
Jian-Qiao Sun ◽  
C. S. Hsu
Keyword(s):  
Stochastic Systems ◽  
Transition Probability ◽  
Transition Probability Matrix ◽  
Mapping Method ◽  
Cell Mapping ◽  
Generalized Cell Mapping ◽  
One Step ◽  
The Mean ◽  
Step Transition ◽  
The One

In this paper a statistical error analysis of the generalized cell mapping method for both deterministic and stochastic dynamical systems is examined, based upon the statistical analogy of the generalized cell mapping method to the density estimation. The convergence of the mean square error of the one step transition probability matrix of generalized cell mapping for deterministic and stochastic systems is studied. For stochastic systems, a well-known trade-off feature of the density estimation exists in the mean square error of the one step transition probability matrix, which leads to an optimal design of generalized cell mapping for stochastic systems. The conclusions of the study are illustrated with some examples.

Fuzzy Logic and Cell to Cell Mapping

1996 ◽  
Author(s):  
D. Edwards ◽  
H. T. Choi ◽  
J. Canning
Keyword(s):  
Fuzzy Logic ◽  
Nonlinear System ◽  
Nonlinear Systems ◽  
Chaotic System ◽  
Transition Probability ◽  
Transition Probability Matrix ◽  
Cell Mapping ◽  
Generalized Cell Mapping ◽  
Simple Cell Mapping

Abstract Nonlinear systems are important in many fields of science, mathematics, and engineering. In recent years, simple cell mapping (SCM) and generalized cell mapping (GCM) methods have been proposed and successfully used to analyze nonlinear systems. The GCM method requires the determination of a transition probability matrix. In a manner similar to GCM, we use fuzzy logic to calculate a transition possibility matrix for a nonlinear system. This matrix can then be used to establish the statistical properties of strange attractors associated with a chaotic system. We analyze a chaotic system using fuzzy logic to demonstrate this approach and then compare our result with the GCM method.

Stochastic Response of a Vibro-Impact System via a New Impact-to-Impact Mapping

2021 ◽  
Vol 31 (08) ◽  
pp. 2150139
Author(s):  
Liang Wang ◽  
Bochen Wang ◽  
Jiahui Peng ◽  
Xiaole Yue ◽  
Wei Xu
Keyword(s):  
Transition Probability ◽  
Transition Probability Matrix ◽  
Significant Feature ◽  
Stochastic Response ◽  
Impact Surface ◽  
Impact System ◽  
The Matrix ◽  
Step Transition ◽  
The One ◽  
The Impact

In this paper, a new impact-to-impact mapping is constructed to investigate the stochastic response of a nonautonomous vibro-impact system. The significant feature lies in the choice of Poincaré section, which consists of impact surface and codimensional time. Firstly, we construct a new impact-to-impact mapping to calculate the one-step transition probability matrix from a given impact to the next. Then, according to the matrix, we can investigate the stochastic responses of a nonautonomous vibro-impact system at the impact instants. The new impact-to-impact mapping is smooth and it effectively overcomes the nondifferentiability caused by the impact. A linear and a nonlinear nonautonomous vibro-impact systems are analyzed to verify the effectiveness of the strategy. The stochastic P-bifurcations induced by the noise intensity and system parameters are studied at the impact instants. Compared with Monte Carlo simulations, the new impact-to-impact strategy is accurate for nonautonomous vibro-impact systems with arbitrary restitution coefficients.

Studying the Global Bifurcation Involving Wada Boundary Metamorphosis by a Method of Generalized Cell Mapping with Sampling-Adaptive Interpolation

2018 ◽  
Vol 28 (02) ◽  
pp. 1830003 ◽  
Author(s):  
Xiao-Ming Liu ◽  
Jun Jiang ◽  
Ling Hong ◽  
Dafeng Tang
Keyword(s):  
Global Bifurcation ◽  
Mapping Method ◽  
Computational Time ◽  
Cell Mapping ◽  
Third Order ◽  
Pendulum System ◽  
Generalized Cell Mapping ◽  
Adaptive Interpolation ◽  
One Step ◽  
Probability Transition Matrix

In this paper, a new method of Generalized Cell Mapping with Sampling-Adaptive Interpolation (GCMSAI) is presented in order to enhance the efficiency of the computation of one-step probability transition matrix of the Generalized Cell Mapping method (GCM). Integrations with one mapping step are replaced by sampling-adaptive interpolations of third order. An explicit formula of interpolation error is derived for a sampling-adaptive control to switch on integrations for the accuracy of computations with GCMSAI. By applying the proposed method to a two-dimensional forced damped pendulum system, global bifurcations are investigated with observations of boundary metamorphoses including full to partial and partial to partial as well as the birth of fully Wada boundary. Moreover GCMSAI requires a computational time of one thirtieth up to one fiftieth compared to that of the previous GCM.

A Cell Mapping Method for Nonlinear Deterministic and Stochastic Systems—Part II: Examples of Application

1986 ◽  
Vol 53 (3) ◽  
pp. 702-710 ◽  
Author(s):  
H. M. Chiu ◽  
C. S. Hsu
Keyword(s):  
Present Method ◽  
Stochastic Systems ◽  
Random Excitation ◽  
Mapping Method ◽  
Cell Mapping ◽  
Generalized Cell Mapping ◽  
Deterministic Systems ◽  
Strongly Nonlinear ◽  
Stochastic Problems ◽  
A Cell

In this second part of the two-part paper we demonstrate the viability of the compatible simple and generalized cell mapping method by applying it to various deterministic and stochastic problems. First we consider deterministic problems with non-chaotic responses. For this class of problems we show how system responses and domains of attraction can be obtained by a refining procedure of the present method. Then, we consider stochastic problems with stochasticity lying in system parameters or excitation. Next, deterministic systems with chaotic responses are considered. By the present method, finding the statistical responses of such systems under random excitation also presents no difficulties. Some of the systems studied here are well-known. New results are, however, also obtained. These are results on Duffing systems with a stochastic coefficient, the global results of a Duffing system shown in Section 4, the results on strongly nonlinear Duffing systems under random excitations reported in Section 7.2, and the strange attractor results for systems subjected to random excitations.

GLOBAL ANALYSIS OF STOCHASTIC BIFURCATION IN DUFFING SYSTEM

2003 ◽  
Vol 13 (10) ◽  
pp. 3115-3123 ◽  
Author(s):  
WEI XU ◽  
QUN HE ◽  
TONG FANG ◽  
HAIWU RONG
Keyword(s):  
Global Analysis ◽  
Sudden Change ◽  
Harmonic Excitation ◽  
Mapping Method ◽  
Invariant Sets ◽  
Stochastic Bifurcation ◽  
Cell Mapping ◽  
Generalized Cell Mapping ◽  
Duffing System ◽  
Stable Invariant

Stochastic bifurcation of a Duffing system subject to a combination of a deterministic harmonic excitation and a white noise excitation is studied in detail by the generalized cell mapping method using digraph. It is found that under certain conditions there exist two stable invariant sets in the phase space, associated with the randomly perturbed steady-state motions, which may be called stochastic attractors. Each attractor owns its attractive basin, and the attractive basins are separated by boundaries. Along with attractors there also exists an unstable invariant set, which might be called a stochastic saddle as well, and stochastic bifurcation always occurs when a stochastic attractor collides with a stochastic saddle. As an alternative definition, stochastic bifurcation may be defined as a sudden change in character of a stochastic attractor when the bifurcation parameter of the system passes through a critical value. This definition applies equally well either to randomly perturbed motions, or to purely deterministic motions. Our study reveals that the generalized cell mapping method with digraph is also a powerful tool for global analysis of stochastic bifurcation. By this global analysis the mechanism of development, occurrence and evolution of stochastic bifurcation can be explored clearly and vividly.

Influence of contrasting canopy architecture on yield of maize hybrids

2020 ◽  
Vol 2 (1) ◽  
pp. 21-26
Author(s):  
Ahsan Areeb ◽  
Rana Nauman Shabir ◽  
Saad Ullah ◽  
Noman Ramzan
Keyword(s):  
Block Design ◽  
Research Area ◽  
Canopy Architecture ◽  
Maize Crop ◽  
Yield Attributes ◽  
Maize Hybrids ◽  
Standard Procedures ◽  
Significant Difference ◽  
Almost All ◽  
The Impact

The yield and productivity of maize is influenced by several factors of which the orientation of canopy in time and space is a crucial one. A field study was undertaken at Agronomic Research Area, Department of Agronomy, Faculty of Agricultural Sciences Technology, Bahauddin Zakariya University, Multan during autumn 2015 to compare the impact of contrasting canopy architecture on yield and yield components of maize hybrids. Two maize hybrids with contrasting canopy architecture viz., Pioneer 30Y87 (semi-erect canopy) and Monsanto’s DK6789 (droopy canopy architecture) were sown in 75 cm spaced ridges. The experiment was laid out in Randomized Complete Block Design (split-plot arrangement) with three replications. Data on yield attributes of maize were recorded following standard procedures. Differences among treatments’ means were compared using Tukey’s honest significant difference test (HSD) at 5% probability level. Results revealed that there were significant differences among hybrids regarding the number of grains per cob, the 1000-grain weight and ultimately the yield of maize crop. Almost all of the parameters were significantly affected by Hybrid 30Y87 and it attained the grain yield. This was due to its better light attenuating properties and the shading effect of its canopy which helped in suppressing the weeds growing underneath.

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