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We consider feedback predictive control of a discrete nonhomogeneous Markov jump system with nonsymmetric constraints. The probability transition of the Markov chain is modelled as a time-varying polytope. An ellipsoid set is utilized to construct an invariant set in the predictive controller design. However, when the constraints are nonsymmetric, this method leads to results which are over conserved due to the geometric characteristics of the ellipsoid set. Thus, a polyhedral invariant set is applied to enlarge the initial feasible area. The results obtained are for a more general class of dynamical systems, and the feasibility region is significantly enlarged. A numerical example is presented to illustrate the advantage of the proposed method.
Scaling laws reveal the fundamental property of phenomena, namely self-similarity - repeating in time and/or space - which substantially simplifies the mathematical modelling of the phenomena themselves. This book begins from a non-traditional exposition of dimensional analysis, physical similarity theory, and general theory of scaling phenomena, using classical examples to demonstrate that the onset of scaling is not until the influence of initial and/or boundary conditions has disappeared but when the system is still far from equilibrium. Numerous examples from a diverse range of fields, including theoretical biology, fracture mechanics, atmospheric and oceanic phenomena, and flame propagation, are presented for which the ideas of scaling, intermediate asymptotics, self-similarity, and renormalisation were of decisive value in modelling.
We provide an introduction to enumerating and constructing invariants of group representations via character methods. The problem is contextualized via two case studies, arising from our recent work: entanglement invariants for characterizing the structure of state spaces for composite quantum systems; and Markov invariants, a robust alternative to parameter-estimation intensive methods of statistical inference in molecular phylogenetics.
We consider infinite-horizon optimal control problems. The main idea is to convert the problem into an equivalent finite-horizon nonlinear optimal control problem. The resulting problem is then solved by means of a direct method using Haar wavelets. A local property of Haar wavelets is applied to simplify the calculation process. The accuracy of the present method is demonstrated by two illustrative examples.
We propose a new Adomian decomposition method (ADM) using an integrating factor for the Emden–Fowler equation. With this method, we are able to solve certain Emden–Fowler equations for which the traditional ADM fails. Numerical results obtained from testing our linear and nonlinear models are far more reliable and efficient than those from existing methods. We also present a complete error analysis and a convergence criterion for this method. One drawback of the traditional ADM is that the interval of convergence of the Adomian truncated series is very small. Some techniques, such as Pade approximants, can enlarge this interval, but they are too complicated. Here, we use a continuation technique to extend our method to a larger interval.
We consider a distributed optimization problem over a multi-agent network, in which the sum of several local convex objective functions is minimized subject to global convex inequality constraints. We first transform the constrained optimization problem to an unconstrained one, using the exact penalty function method. Our transformed problem has a smaller number of variables and a simpler structure than the existing distributed primal–dual subgradient methods for constrained distributed optimization problems. Using the special structure of this problem, we then propose a distributed proximal-gradient algorithm over a time-changing connectivity network, and establish a convergence rate depending on the number of iterations, the network topology and the number of agents. Although the transformed problem is nonsmooth by nature, our method can still achieve a convergence rate, ${\mathcal{O}}(1/k)$, after $k$ iterations, which is faster than the rate, ${\mathcal{O}}(1/\sqrt{k})$, of existing distributed subgradient-based methods. Simulation experiments on a distributed state estimation problem illustrate the excellent performance of our proposed method.
The last thirty years have seen great leaps forward in the subject of magnetoconvection. Computational techniques can now explain exotic nonlinear behaviour, transition to chaos and the formation of structures that can be observed on the surface of the Sun. Here, two leading experts present the current state of knowledge of the subject. They provide a mathematical and numerical treatment of the interactions between electrically conducting fluids and magnetic fields that lead to the complex structures and rich behaviour observed on the Sun and other stars, as well as in the interiors of planets like the Earth. The authors' combined analytical and computational approach provides a model for the study of a wide range of related problems. The discussion includes bifurcation theory, chaotic behaviour, pattern formation in two and three dimensions, and applications to geomagnetism and to the properties of sunspots and other features at the solar surface.
In this final chapter we focus on the interactions between convection, magnetic fields and rotation in stars that, like our Sun, possess deep outer convection zones, with the aim of relating theory to observations. Following on from the treatment of planetary dynamos in Chapter 7, we begin by considering the large-scale fields that are responsible for the solar cycle and survey attempts to model solar and stellar dynamos, ranging from mean-field dynamo theory to the results of the latest massive computations (Charbonneau 2010).
Then we turn to small-scale behaviour at the solar surface. Over the past two decades detailed observations – from the ground, from the stratosphere and from space – have revealed a wealth of detailed information about the structure and properties of magnetic features on the Sun and on other magnetically active stars. Although the idealized theoretical models that we have described in previous chapters do explain the general behaviour of magnetic fields at the surface of a vigorously convecting star, any more detailed confrontation of theory with observations demands a more precise description of the stellar plasma. Two properties are particularly important. The first is the role of ionization: in the Sun, hydrogen is ionized just below the visible photosphere, with resulting changes to the equation of state and the value of γ that affect the superadiabatic gradient and lead to the presence of a deep convection zone (Stix 2002).
The original motivation for studying magnetoconvection came from the interplay between magnetic fields and convection that is observed in sunspots. Since then this subject has developed into a fascinating and important topic in its own right. We therefore decided to write a comprehensive monograph that would cover all aspects of magnetoconvection from the viewpoint of applied mathematics, and as a branch of astrophysical (or geophysical) fluid dynamics. Thus we shall emphasize the role of nonlinear dynamics, and focus on idealized model problems rather than on ambitious realistic simulations.
The properties of convection in an electrically conducting fluid with an imposed magnetic field are interesting not only in themselves but also as the richest example of double-diffusive behaviour. Linear theory allows both steady and oscillatory solutions, while theoretical descriptions of nonlinear behaviour demonstrate the power of bifurcation theory, with examples of bifurcation sequences that lead to chaos, as well as of group-theoretic applications to pattern selection. These mathematical results can all be related to carefully constructed numerical experiments.
Although we shall adopt an applied mathematical approach, our discussion is particularly relevant to the behaviour of magnetic fields at the surface of the Sun, which are now being observed in unprecedented detail, both from the ground and from space. Convection also interacts with magnetic fields in the solar interior, as it does in other stars, and is a key component of solar and stellar dynamos.
We have seen that convection may set in at either a Hopf or a pitchfork bifurcation, giving rise to branches of nonlinear oscillatory or steady motion. In this chapter we consider weakly and mildly nonlinear behaviour, in regimes that are accessible to an analytical approach, without having to rely on large-scale computation. Our treatment relies on mathematical developments in nonlinear dynamics – a subject that has its roots in the work of Poincaré more than a century ago but has grown explosively during the past few decades. In what follows we shall adopt a straightforward approach that is aimed at traditional applied mathematicians rather than at experts in nonlinear mathematics. Magnetoconvection provides a rich and fascinating demonstration of the power of bifurcation theory, and of its ability to explain a wide range of interactions between branches of solutions that may be stable or unstable, steady, oscillatory or chaotic.
We shall confine our attention here to idealized models of Boussinesq magnetoconvection, and focus on two-dimensional behaviour. In subsequent chapters these restrictions will be progressively relaxed. We shall mainly be concerned with imposed magnetic fields that are vertical, but horizontal fields will be considered briefly in the final subsection. As in Section 3.1.4, we assume that the velocity u and the magnetic field B are confined to the xz-plane and independent of y.
In this chapter we penetrate further into the nonlinear domain, relying principally on the results of careful numerical experiments, and confining our attention to the simplest and most thoroughly studied configurations. Our primary aim is to extract qualitative understanding from the computations. Once interpreted, they provide a basis for investigating the more complicated structures and patterns that will be treated later in the book.
We begin by extending the mildly nonlinear results in Chapter 4 to cover convection in a rectangular box when the magnetic Reynolds number is large and the magnetic field becomes dynamically important. Then we study the analogous problem in a cylindrical domain with axial symmetry imposed. Next we return to Cartesian models and to the chaotic behaviour that was introduced in Section 4.3, in order to confirm that the Shilnikov effect is present in the full system; in addition, we find a regime with Lorenz-like chaos. Thereafter we consider the effects of relaxing the lateral constraints and thereby allowing travelling waves, together with steady convection in tilted cells and vigorous pulsating waves. That leads us to consider patterns of convection in extended regions, where rolls are modulated at longer wavelengths and localized (or isolated) states can appear. Then we proceed to the strong field limit, and consider behaviour when cells are vertically elongated and very slender. Finally, we discuss the effects of inclined magnetic fields on nonlinear convection.
In this chapter we introduce the effects of rotation into the study of magnetoconvection. While these effects can safely be neglected when discussing the dynamics of the solar photosphere, since typical timescales are much less than a solar day, the large-scale motions occurring deeper in the solar convection zone and in the Earth's liquid core are strongly affected by rotation. Indeed, rotation would appear to be a crucial ingredient in the dynamo mechanisms that are responsible for the geomagnetic field and the solar magnetic cycle. A full discussion of dynamo theory is outside the scope of this book (though see, for example, Dormy and Soward 2007) but we shall discuss dynamo models in which convection plays a prominent role. As such, we shall depart later in this chapter from consideration of convective flows in simple planar models and in addition discuss what happens in spherical geometries.
A necessary preliminary to understanding the complex interaction of magnetic fields with rotating convection is a discussion of the rotating, nonmagnetic case. This is first done in a Cartesian geometry. Then the effect of a vertical magnetic field is introduced. We restrict ourselves to the problem of convection in a layer rotating about a vertical axis. Then we can discuss the effects of a vertical magnetic field (this makes comparison with previous chapters easier, but such a configuration is not one that can readily be recognized in nature).