全局分析的广义胞映射图论方法

应用广义胞映射理论的离散连续状态空间为胞状态空间的基本概念,依循Ｈｓｕ的将偏序集和图论理论引入广义胞映射的思想,以集论和图论理论为基础,提出了进行非线性动力系统全局分析的广义胞映射图论方法．在胞状态空间上,定义二元关系,建立了广义胞映射动力系统与图的对应关系,给出了自循环胞集和永久自循环胞集存在判别定理的证明,这样可借助国论的理论和算法来确定动力系统的全局性质．应用图的压缩方法,对所有的自循环胞集压缩后,在全局瞬态分析计算中瞬态胞的总数目得到有效地减少,并能借助于图的算法有效地实现全局瞬态的拓扑排序．在整个定性性质的分析计算中,仅采用布尔运算．     

用胞映射方法讨论GKDV方程全局吸引域

本文用胞映射方法画出了GKDV方程未受扰系统和受扰系统的全局吸引域、r步吸引域。     

胞映射方法的研究和进展

介绍了胞映射方法的研究和进展. 归纳了目前胞映射方法的几种主要研究方法, 主要包括简单胞映射、广义胞映射、图胞映射、图胞映射的符号分析方法、图胞映射的面向集合方法、邻接胞映射、庞加莱型的简单胞映射、插值胞映射以及胞参照点映射方法, 分析了各类方法的基本特点和特色, 简述了这几种胞映射方法的最新国内外进展, 综述了胞映射方法在控制及相关领域的应用研究及进展, 给出了胞映射方法研究的一些展望, 提出了胞映射方法研究可能率先突破的几个研究方向.     

胞映射搜索最优控制路径的新策略

在胞映射求解最优控制问题的现有方法的基础上，提出了一种利用胞映射搜索最优控制路径的新策略。该策略基于负步长逆向数值积分技巧，采用了一种新的搜索过程，使得求解问题的效率大为提高。同现有的方法相比，新策略节省了几倍，甚至十几倍的时间。而且计算结果可靠，有很强的工程应用价值，为求解高维的最优控制问题可能会提供一定的基础。     

非线性动力系统全局分析的变胞胞映射法与转子／轴承系统的全局稳定性

在Ｐｏｉｎｃａｒｅ映射及胞映理论的基础上，提出了一种非线性动力系统全局分析的新方法－－变胞胞映射法，这种新方法改变了原胞映射法中胞在胞空间分布的不合理性及运算逻辑的不合理性，更适用于高维、大求解域非线性动力系统的求解。应用此方法，对具有非线性油膜力的Ｊｅｆｆｃｏｔ转子轴承系统进行了全局分析，绘制了系统分岔后的全局吸引域图，解释了一些工程中常见的非线性现象。     

全局分析的胞参照点映射迭代方法：理论及多尺度参照技术

胞参照点遇射迭代方法，建立了一个胞参照系来识别状态空间中的子区（胞）装配了特性函数后，胞纱就可以作为者和记录者由通过一佣子区的轨道信息去引出此子区的局部动力学，可以在保持点映射的精度，大大减少计算量。文中给出方法的理论基础和多尺度胞参照技术，后者用来实用时优化胞参照系，最后给出一个例子，示出本法不只可以提高吸引域的精度和效率，还有探查其他动力特性的潜力。     

非线性动力学系统全局分析之外的胞映射方法新发展

在20世纪80年代由徐皆苏教授创建的胞映射方法一直受非线性科学界同仁的欢迎.近几年胞映射方法有了许多新的应用和算法.本文介绍了一些控制应用和算法的文献.另外,还介绍和讨论胞映射方法应用与多目标优化问题的研究和方法,多目标优化控制设计和非线性代数方程找零解.文中指出胞映射方法在井行计算的帮助下,现在可以解决中等高维空间中的各类问题,新的应用还会不断出现.     

Duffing振子奇怪吸引子的简单胞映射计算

本文运用简单胞映射理论,计算出了有阻尼Ｄｕｆｆｉｎｇ振子的强迫振动在一定参数条件下存在的奇怪吸引子,算法简单,结果理想,通过实例证明了简单胞映射理论在计算混沌问题方面的有效性．     

一种最优控制的胞映射算法

由Hsu提出的利用胞映射进行最优控制的方法可以发展成实用的工程控制技术.本文以研究算法为出发点,利用胞映射的特性,结合实际的计算与可能,作了一系列旨在提高计算速度和节省内存的改进;并给出了简单有效的区分同耗最优控制对的统一的方法.使用平常的微型计算机也能有效地解决实际工程问题的最优控制.     

非光滑动力系统胞映射计算方法

针对非光滑动力学系统特点,在胞映射思想基础上,引入拉回积分等分析手段,得到了非光滑系统吸引子和吸引域的胞映射计算方法.并以一类碰振系统为例,给出了其吸引子和具有复杂分形边界的吸引域,并验证了该方法的有效性.     

The adjoining cell mapping and its recursive unraveling,part II: Application to selected problems

Several applications of the adjoining cell mapping technique are provided here by employing the adaptive mapping unraveling algorithm to analyze smooth and pathological autonomous dynamical systems. The performance of an implementation of recursive unraveling algorithm is also illustrated regarding its low memory requirements for computational purposes when compared with the simple cell mapping method. The applications considered here illustrate the effectiveness of the adjoining cell mapping technique in its ability to determine limit cycles and to unravel nonstandard dynamics. The advantages of this new technique of global analysis over the simple cell mapping method are discussed.     

The adjoining cell mapping and its recursive unraveling,part I: Description of adaptive and recursive algorithms

A new type of cell mapping, referred to as an adjoining cell mapping, is developed in this paper for autonomous dynamical systems employing the cellular state space. It is based on an adaptive time integration employed to compute an associated cell mapping for the system. This technique overcomes the problem of determining an appropriate duration of integration time for the simple cell mapping method. Employing the adjoining mapping principle, the first type of algorithm developed here is an adaptive mapping unraveling algorithm to determine equilibria and limit cycles of the dynamical system in a way similar to that of the simple cell mapping. In addition, it is capable of providing useful information regarding the behavior of dynamical systems possessing pathological dynamics and of systems with rapidly changing vector field. The adjoining property inherent in the adjoining cell mapping method, in general, permits development of new recursive algorithms for unraveling dynamics. The required computer memory for a practical implementation of such algorithms is considerably less than that required by the simple cell mapping algorithm since they allow for a recursive partitioning of state space for trajectory analysis. The second type of algorithm developed in this paper is a recursive unraveling algorithm based on adaptive integration and recursive partitioning of state space into blocks of cells with a view toward its practical implementation. It can find equilibria of the system in the same manner as the simple cell mapping method but is more efficient in locating periodic solutions.     

A nonlinear oscillatory system subjected to driving forces of elliptic type

The aim of this paper is to show how Jacobi elliptic functions in combination with the averaging and the harmonic balance methods can be applied to obtain the approximate solution of two coupled, ordinary differential equations having a spring with cubic nonlinearity and subjected to driving forces of elliptic type. By an appropriate choice of the system parameter values, it is possible to show that our derived solution represents the exact steady-state solution of the undamped Duffing equation with driving force of elliptic type. At the end of this work, we also demonstrate the validity of our derived solution by comparing the amplitude–time response curves with those of the numerical integration solutions.     

On the multiple-attractor coexsting system with parameter uncertainties using generalized cell mapping method

In this paper the generalized cell mapping (GCM) method is used to study multiple-attractor coexisting system with parameter uncertainties. The effects that the uncertain parameters has on the global properties of the system are presented. And It is obtained that the attractor with much smaller value of protect thickness, will disappear firstly with the degree of the uncertainty of parameter increasing. Project supported by the National Natural Science Foundation of China (19672046)     

含非线性摩擦系数的单自由度颤振系统全局动力学行为数值研究

摩擦系数模型取更具普适性的Stribeck非线性模型,基于事件驱动理论,利用C与Matlab联合仿真的方法开发了干摩擦颤振问题的快速求解程序。给出改进的胞映射算法,对含非线性摩擦的单自由度摩擦颤振系统的演化过程及其全局性态进行数值分析和研究,得到系统在任意的初始状态下的响应特性、系统收敛域的数值计算分析结果。分析结果表...     

Stochastic P-bifurcation analysis of a fractional smooth and discontinuous oscillator via the generalized cell mapping method

The smooth and discontinuous oscillator with fractional derivative damping under combined harmonic and random excitations is investigated in this paper. The short memory principle is introduced so that the evolution process of the oscillator with fractional derivative damping can be described by the Markov chain. Then the stochastic generalized cell mapping method is used to obtain the steady-state probability density functions of the response. The stochastic response and bifurcation of the oscillator with fractional derivative damping are discussed in detail. We found that both the smoothness parameter, the noise intensity, the amplitude and frequency of the harmonic force can induce the occurrence of stochastic P-bifurcation in the system. Monte Carlo simulation verifies the effectiveness of the method we adopt in the paper.     

Stochastic response analysis of noisy system with non-negative real-power restoring force by generalized cell mapping method

The stochastic response of a noisy system with non-negative real-power restoring force is investigated. The generalized cell mapping (GCM) method is used to compute the transient and stationary probability density functions (PDFs). Combined with the global properties of the noise-free system, the evolutionary process of the transient PDFs is revealed. The results show that stochastic P-bifurcation occurs when the system parameter varies in the response analysis and the stationary PDF evolves from bimodal to unimodal along the unstable manifold during the bifurcation.     

Stochastic bifurcation in duffing system subject to harmonic excitation and in presence of random noise

A global analysis of stochastic bifurcation in a special kind of Duffing system, named as Ueda system, subject to a harmonic excitation and in presence of random noise disturbance is studied in detail by the generalized cell mapping method using digraph. It is found that for this dissipative system there exists a steady state random cell flow restricted within a pipe-like manifold, the section of which forms one or two stable sets on the Poincare cell map. These stable sets are called stochastic attractors (stochastic nodes), each of which owns its attractive basin. Attractive basins are separated by a stochastic boundary, on which a stochastic saddle is located. Hence, in topological sense stochastic bifurcation can be defined as a sudden change in character of a stochastic attractor when the bifurcation parameter of the system passes through a critical value. Through numerical simulations the evolution of the Poincare cell maps of the random flow against the variation of noise intensity is explored systematically. Our study reveals that as a powerful tool for global analysis, the generalized cell mapping method using digraph is applicable not only to deterministic bifurcation, but also to stochastic bifurcation as well. By this global analysis the mechanism of development, occurrence, and evolution of stochastic bifurcation can be explored clearly and vividly.     

On the effect of constraint parameters on the generalized displacement control method

In this work, we investigate the generalized displacement control method (GDCM) and provide a modification (MGDCM) that results in an equivalent constraint equation as that of the linearized cylindrical arc-length control method (LCALCM). Through numerical examples, we illustrate that the MGDCM is more robust than the standard GDCM in capturing equilibrium paths in regions of high curvature. Moreover, we also provide a geometric and physical interpretation of the method, which sheds light on the general class of path following methods in structural mechanics.     

Fast computation of the wall distance in unsteady Eulerian fluid-structure computations

Highly nonlinear, turbulent, dynamic, fluid-structure interaction problems characterized by large structural displacements and deformations, as well as self-contact and topological changes, are encountered in many applications. For such problems, the Eulerian computational framework, which is often equipped with an embedded (or immersed) boundary method for computational fluid dynamics, is often the most appropriate framework. In many circumstances, it requires the computation of the time-dependent distance from each active mesh vertex of the embedding mesh to the nearest embedded discrete surface. Such circumstances include, for example, modeling turbulence using the Spalart-Allmaras or detached eddy simulation turbulence models and performing adaptive mesh refinement in order to track the boundary layer. Evaluating at each time step the distance to the wall is computationally prohibitive, particularly in the context of explicit-explicit fluid-structure time-integration schemes. Hence, this paper presents two complementary approaches for reducing this computational cost. The first one recognizes that many quantities depending on the wall distance are relatively insensitive to its inaccurate evaluation in the far field. Therefore, it simplifies a state-of-the-art algorithm for computing the wall distance accordingly. The second approach relies on an effective wall distance error estimator to update the evaluation of the wall distance function only when otherwise, a quantity of interest that depends on it would become tainted by an unacceptable level of error. The potential of combining both approaches for dramatically accelerating the computation of the wall distance is demonstrated with the Eulerian simulation of the inflation of a disk-gap-band parachute system in a supersonic airstream.