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1987 | Buch

Cell-to-Cell Mapping

A Method of Global Analysis for Nonlinear Systems

verfasst von: C. S. Hsu

Verlag: Springer New York

Buchreihe : Applied Mathematical Sciences

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Über dieses Buch

For many years, I have been interested in global analysis of nonlinear systems. The original interest stemmed from the study of snap-through stability and jump phenomena in structures. For systems of this kind, where there exist multiple stable equilibrium states or periodic motions, it is important to examine the domains of attraction of these responses in the state space. It was through work in this direction that the cell-to-cell mapping methods were introduced. These methods have received considerable development in the last few years, and have also been applied to some concrete problems. The results look very encouraging and promising. However, up to now, the effort of developing these methods has been by a very small number of people. There was, therefore, a suggestion that the published material, scattered now in various journal articles, could perhaps be pulled together into book form, thus making it more readily available to the general audience in the field of nonlinear oscillations and nonlinear dynamical systems. Conceivably, this might facilitate getting more people interested in working on this topic. On the other hand, there is always a question as to whether a topic (a) holds enough promise for the future, and (b) has gained enough maturity to be put into book form. With regard to (a), only the future will tell. With regard to (b), I believe that, from the point of view of both foundation and methodology, the methods are far from mature.

Inhaltsverzeichnis

Frontmatter
Chapter 1. Introduction and Overview
Abstract
Nonlinear systems appear in many scientific disciplines, including engineering, physics, chemistry, biology, economics, and demography. Methods of analysis of nonlinear systems, which can provide a good understanding of their behavior, have, therefore, wide applications. In the classical mathematical analysis of nonlinear systems (Lefschetz [1957], Bogoliubov and Mitropolsky [1961], Minorsky [1962], Cesari [1963], Hayashi [1964], Andronov et al. [1973], and Nayfeh and Mook [1979]), once the equation of motion for a system has been formulated, one usually tries first to locate all the possible equilibrium states and periodic motions of the system. Second, one studies the stability characteristics of these solutions. As the third task, one may also study how these equilibrium states and periodic solutions evolve as the system parameters are changed. This leads to various theories of bifurcation (Marsden and McCracken [1976], boss and Joseph [1980], and Chow and Hale [1982]). Each of these tasks can be a very substantial and difficult one. In recent years the existence and importance of strange attractors have been recognized, and one now attempts to include these more exotic system responses, if they exist, in the first three types of investigations (Lichtenberg and Lieberman [1982] and Guckenheimer and Holmes [1983]).
C. S. Hsu
Chapter 2. Point Mapping
Abstract
In system analysis a dynamical system of finite degrees of freedom is often modeled in the form of an ordinary differential equation
$$\dot x = F\left( {x,t,\mu } \right);x \in {\Bbb {R}^N},t \in \Bbb {R},\mu \in {\Bbb {R}^K}, $$
(2.1.1)
where x is an N-dimensional state vector, t the time variable, μ a K-dimensional parameter vector, and F a vector-valued function of x, t,and μ. A motion of the system with a given μ defines a trajectory in the N-dimensional state space of the system which will be denoted by X N . We assume that F(x, t, μ) satisfies the Lipschitz condition so that uniqueness of solutions is assured. For cases where F(x, t,μ) may be such that the state variables of the solution suffer discontinuities at discrete instants of time, we assume that sufficient information is provided and the physical laws governing the discontinuities are known so that the magnitudes of the discontinuities at these instants can be deter­mined uniquely without ambiguity.
C. S. Hsu
Chapter 3. Analysis of Impulsive Parametric Excitation Problems by Point Mapping
Abstract
In this chapter we consider a class of mechanical systems for which the governing point mappings can be obtained exactly in analytical form. Thus, we can have confidence that the results obtained from point mapping analyses truly reflect the behavior of the original systems, no matter how complex or unexpected they may be.
C. S. Hsu
Chapter 4. Cell State Space and Simple Cell Mapping
Abstract
In Section 1.4 we have mentioned certain physical and mathematical factors which provide motivations to consider a state space not as a continuum but as a collection of state cells, with each cell being taken as a state entity. There are many ways to obtain a cell structure over a given Euclidean state space. The simplest way is to construct a cell structure consisting of rectangular parallelepipeds of uniform size. Let x i , i = 1, 2,…, N,be the state variables of the state space. Let the coordinate axis of a state variable x i be divided into a large number of intervals of uniform interval size h i .
C. S. Hsu
Chapter 5. Singularities of Cell Functions
Abstract
In order to motivate certain notions about singularities of cell functions we shall first examine the one- and two-dimensional cell functions in Sections 5.1 and 5.2. With these low-dimensional functions the basic geometrical ideas are much easier to appreciate. Before proceeding, let us introduce some terms which will be found convenient in the following discussions.
C. S. Hsu
Chapter 6. A Theory of Index for Cell Functions
Abstract
In this chapter we present a theory of index for cell functions. The development will be based on the utilization of simplicial structures discussed in the last chapter and the index theory for N-dimensional vector fields discussed in Section 2.8.
C. S. Hsu
Chapter 7. Characteristics of Singular Entities of Simple Cell Mappings
Abstract
For a given simple cell mapping C(z) there is a cell mapping increment function F(z, C K ) associated with the mapping C K (z). In Chapter 5 we have considered the singular entities of such cell functions. These include non-degenerate and degenerate singular k-multiplets m k , kN + 1, and cores of singular multiplets. We recall here that for dynamical systems governed by ordinary differential equations (Coddington and Levinson [1955], Arnold [1973]) and for point mapping dynamical systems (Hsu [1977], Bernussou [1977]), the singular points of the vector fields governing the systems can be further classified according to their stability character. In this spirit one may wish to classify singular entities of cell functions according to their “stability” character and to see how they influence the local and global behavior of the cell mapping systems. On this question a special feature of cell mappings immediately stands out. Since a cell function maps an N-tuple of integers into an N-tuple of integers, the customary continuity and differentiability arguments of the classical analysis cannot be used, at least not directly. Evidently, a new framework is needed in order to delineate various mapping properties of the singular entities of cell functions.
C. S. Hsu
Chapter 8. Algorithms for Simple Cell Mappings
Abstract
In this chapter we turn to certain computational aspects of simple cell mappings. We shall discuss two topics: locating all the singular entities of the cell function associated with a simple cell mapping and having a procedure which will allow us to determine the global behavior of the mapping in a very efficient way.
C. S. Hsu
Chapter 9. Examples of Global Analysis by Simple Cell Mapping
Abstract
In the last five chapters the simple cell mappings are studied in their own right as transformations of an N-tuple of integers to an N-tuple of integers. In this chapter we use simple cell mappings as tools to investigate the global behavior of dynamical systems governed by point mappings and differential equations. We first review the center point method by which a simple cell mapping can be constructed for a point mapping or for an ordinary differential equation governing the system. Next, we discuss a special technique called compactification which allows us to construct a simple cell mapping over a finite set of cells S without introducing the concept of sink cell.
C. S. Hsu
Chapter 10. Theory of Generalized Cell Mapping
Abstract
The theory of simple cell mapping discussed in the last few chapters is a simple one. Nevertheless, when it is used as an approximate method to study a nonlinear system governed by a differential equation or a point mapping, it is quite effective in delineating the broad pattern of the global behavior of the system. Since in creating the simple cell mapping only one point within the cell, usually the center point, is used, one cannot expect the method to disclose any structural detail of the system behavior at a scale which is comparable to the cell size. One way to improve the power of the cell mapping method is to incorporate more system dynamics into the mapping. This leads to the generalized cell mapping introduced in Hsu [1981a].
C. S. Hsu
Chapter 11. Algorithms for Analyzing Generalized Cell Mappings
Abstract
In the last chapter we discussed the basic ideas of the theory of generalized cell mapping and some elements of the theory of Markov chains. From the discussion it is obvious that if a normal form of the transition probability matrix can be found, then a great deal of the system behavior is already on hand. To have a normal form (10.3.7) is essentially to know the persistent groups and the transient groups. In Section 10.5 we have seen some simple examples of generalized cell mapping. Those examples involve only a very small number of cells. The normal forms can be obtained merely by inspection. For applications of generalized cell mapping to dynamical systems where a very large number of cells are used, it is an entirely different matter. We need a viable procedure to discover persistent and transient groups and, if possible, the hierarchy among the transient groups.
C. S. Hsu
Chapter 12. An Iterative Method, from Large to Small
Abstract
Consider a dynamical system governed by
$$\dot x = F(x,t,\mu ),x \in {\Bbb {R}^N},t \in \Bbb {R},\mu \in {\Bbb {R}^K}$$
(12.1.1)
.
C. S. Hsu
Chapter 13. Study of Strange Attractors by Generalized Cell Mapping
Abstract
In recent years the phenomenon of strange attractors has received a great deal of attention. The literature is too vast to be quoted extensively here. Many of the papers may be found in Feigenbaum [1980], Ott [1981], Lichtenberg and Lieberman [1982], Jensen and Oberman [1982], Guckenheimer and Holmes [1983], and Hao [1984]. The basic intrigue of this phenomenon comes from the observation that although a strange attractor yields a chaotic motion, the originating system may very well be entirely deterministic in nature. Not only is the phenomenon interesting physically and mathematically, but it also appears in many different fields. Therefore, it deserves to be studied in great depth.
C. S. Hsu
Chapter 14. Other Topics of Study Using the Cell State Space Concept
Abstract
In addition to the various cell mapping topics discussed in the last ten chapters, several others have also been studied recently. These latter ones are mostly still in the exploratory stage of their development. This chapter briefly discusses some of them and also cites the references in which more detailed discussions may be found.
C. S. Hsu
Backmatter
Metadaten
Titel
Cell-to-Cell Mapping
verfasst von
C. S. Hsu
Copyright-Jahr
1987
Verlag
Springer New York
Electronic ISBN
978-1-4757-3892-6
Print ISBN
978-1-4419-3083-5
DOI
https://doi.org/10.1007/978-1-4757-3892-6