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Foundations of Mathematical Optimization
Many books on optimization consider only finite dimensional spaces. This volume is unique in its emphasis: the first three chapters develop optimization in spaces without linear structure, and the analog of convex analysis is constructed for this case. Many new results have been proved specially for this publication. In the following chapters optimization in infinite topological and normed vector spaces is considered. The novelty consists in using the drop property for weak well-posedness of linear problems in Banach spaces and in a unified approach (by means of the Dolecki approximation) to necessary conditions of optimality. The method of reduction of constraints for sufficient conditions of optimality is presented. The book contains an introduction to non-differentiable and vector optimization. Audience: This volume will be of interest to mathematicians, engineers, and economists working in mathematical optimization.
Adaptive Mechanics
Over the last thirty years an abundance of papers have been writ ten on adaptive dynamic control systems. Nevertheless, now it may be predicted with confidence that the adaptive mechanics, a new division, new line of inquiry in one of the violently developing fields of cybernetic mechanics, is emerging. The birth process falls far short of being com pleted. There appear new problems and methods of their solution in the framework of adaptive nonlinear dynamics. Therefore, the present work cannot be treated as a certain polished, brought-to-perfection school textbook. More likely, this is an attempt to show a number of well known scientific results in the parametric synthesis of nonlinear syst...
Functional Nanostructures and Metamaterials for Superconducting Spintronics
This book demonstrates how the new phenomena in the nanometer scale serve as the basis for the invention and development of novel nanoelectronic devices and how they are used for engineering nanostructures and metamaterials with unusual properties. It discusses topics such as superconducting spin-valve effect and thermal spin transport, which are important for developing spintronics; fabrication of nanostructures from antagonistic materials like ferromagnets and superconductors, which lead to a novel non-conventional FFLO-superconducting state; calculations of functional nanostructures with an exotic triplet superconductivity, which are the basis for novel nanoelectronic devices, such as sup...
Estimators for Uncertain Dynamic Systems
When solving the control and design problems in aerospace and naval engi neering, energetics, economics, biology, etc., we need to know the state of investigated dynamic processes. The presence of inherent uncertainties in the description of these processes and of noises in measurement devices leads to the necessity to construct the estimators for corresponding dynamic systems. The estimators recover the required information about system state from mea surement data. An attempt to solve the estimation problems in an optimal way results in the formulation of different variational problems. The type and complexity of these variational problems depend on the process model, the model of uncertainties, and the estimation performance criterion. A solution of variational problem determines an optimal estimator. Howerever, there exist at least two reasons why we use nonoptimal esti mators. The first reason is that the numerical algorithms for solving the corresponding variational problems can be very difficult for numerical imple mentation. For example, the dimension of these algorithms can be very high.
Recent Developments in Automatic Control Systems
This monograph provides an overview of the recent developments in modern control systems including new theoretical findings and successful examples of practical implementation of the control theory in different areas of industrial and special applications. Recent Developments in Automatic Control Systems consists of extended versions of selected papers presented at the XXVI International Conference on Automatic Control "Automation 2020" (October 13–15, 2020, Kyiv, Ukraine) which is the main Ukrainian Control Conference organized by the Ukrainian Association on Automatic Control (national member organization of IFAC) and the National Technical University of Ukraine "Igor Sikorsky Kyiv Polyt...
Interior Point Approach to Linear, Quadratic and Convex Programming
This book describes the rapidly developing field of interior point methods (IPMs). An extensive analysis is given of path-following methods for linear programming, quadratic programming and convex programming. These methods, which form a subclass of interior point methods, follow the central path, which is an analytic curve defined by the problem. Relatively simple and elegant proofs for polynomiality are given. The theory is illustrated using several explicit examples. Moreover, an overview of other classes of IPMs is given. It is shown that all these methods rely on the same notion as the path-following methods: all these methods use the central path implicitly or explicitly as a reference path to go to the optimum. For specialists in IPMs as well as those seeking an introduction to IPMs. The book is accessible to any mathematician with basic mathematical programming knowledge.
