Optimization

"e;Optimal Observation for Cyber-physical Systems"e; addresses the challenge, fundamental to the design of wireless sensor networks (WSNs), presented by the obligatory trade-off between precise estimates and system constraints.

The contents of this monograph fall within the general area of nonlinear functional analysis and applications.

Agent systems are being used to model complex systems like societies, markets and biological systems.

Substantially revised, reorganised and updated, the second edition now comprises eighteen chapters, carefully arranged in a straightforward and logical manner, with many new results and open problems.

Stochastic control is one of the methods being used to find optimal decision-making strategies in fields such as operations research and mathematical finance.

Reliability theory is a major concern for engineers and managers engaged in making high quality products and designing highly reliable systems.

This book is an introduction to game theory from a mathematical perspective.

"e;Process Control Performance Assessment"e; is a guide to the application of control benchmarking to industrial processes.

The purpose of this book is to present a self-contained description of the fun- damentals of the theory of nonlinear control systems, with special emphasis on the differential geometric approach.

"e;Advanced Control of Industrial Processes"e; presents the concepts and algorithms of advanced industrial process control and on-line optimisation within the framework of a multilayer structure.

Based on over 15 years' experience in the design and delivery of successful first-year courses, this book equips undergraduates with the mathematical skills required for degree courses in economics, finance, management and business studies.

This monograph is devoted to the effect of delays on the stability properties of dynamical systems.

While conceptually elegant, the generic formulations of nonlinear model predictive control are not ready to use for the stabilization of fast systems.

Switched linear systems have enjoyed a particular growth in interest since the 1990s.

Recent developments in constrained control and estimation have created a need for this comprehensive introduction to the underlying fundamental principles.

Stochastic geometry is a relatively new branch of mathematics.

The world's best negotiators have moved beyond the conventional wisdom by utilising cutting-edge studies and real-world results.

This book explores recent developments and exciting challenges in operations research and mathematical optimization.

This book explores the urgent quest for sustainable energy solutions by examining potential renewable energy sources that meet global demands.

This book develops robust design and assessment of product and production from viewpoint of system theory, which is quantized with the introduction of brand new concept of preferable probability and its assessment.

This book is devoted to the study of the turnpike phenomenon arising in optimal control theory.

This monograph introduces a new mathematical model in population dynamics that describes two species sharing the same environmental resources in a situation of open hostility.

This book is interdisciplinary and unites several areas of applied probability, statistics, and computational mathematics including computer experiments, optimal experimental design, and global optimization.

Monte Carlo Methods are among the most used, and useful, computational tools available today.

This book presents a comprehensive series of methods in nonsmooth optimization, with a particular focus on their application in stochastic programming and dedicated algorithms for decision-making under uncertainty.

This book delves into the intricate world of interval programming, offering a comprehensive exploration of mathematical programming problems characterized by interval data.

The book aims at endowing any student with a survival toolkit to start safely diving into the realm of Calculus of Variations.

This book covers all the standard introductory topics in classical mechanics, for the first part: Statics (the analysis of forces and moments acting on a mechanical system in equilibrium with its environment).

This handbook delves into the rapidly evolving field of artificial intelligence and optimization, focusing on the intersection of machine learning, combinatorial optimization, and real-world applications in transportation and network design.

This book introduces readers to order analysis and various aspects of deep learning, and describes important connections to optimization, such as nonlinear optimization as well as vector and set optimization.

Control Systems Benchmarks helps control engineers, researchers, and students to evaluate and compare control system performance across a range of critical applications by offering a collection of real-world benchmarks.

Aligning the latest practices, innovations and case studies with academic frameworks and theories, the broad area of multi-criteria and game theory applications in manufacturing and logistics is covered in comprehensive detail.

This practical and authoritative text/reference presents a broad introduction to the optimization methods used specifically in computer vision.

Structured Controllers for Uncertain Systems focuses on the development of easy-to-use design strategies for robust low-order or fixed-structure controllers (particularly the industrially ubiquitous PID controller).

Mathematical models can be used to meet many of the challenges and opportunities offered by modern biology.

This book highlights a unique combination of numerical tools and strategies for handling the challenges of multiphysics simulation, with a specific focus on electromechanical systems as the target application.

Backward stochastic differential equations with jumps can be used to solve problems in both finance and insurance.

This book shows how the use of S-variables (SVs) in enhancing the range of problems that can be addressed with the already-versatile linear matrix inequality (LMI) approach to control can, in many cases, be put on a more unified, methodical footing.

Though the game-theoretic approach has been vastly studied and utilized in relation to economics of industrial organizations, it has hardly been used to tackle safety management in multi-plant chemical industrial settings.

There are many methods of stable controller design for nonlinear systems.

Optimal Control and Optimization of Stochastic Supply Chain Systems examines its subject the context of the presence of a variety of uncertainties.

Stochastic Recursive Algorithms for Optimization presents algorithms for constrained and unconstrained optimization and for reinforcement learning.

Functional analysis owes much of its early impetus to problems that arise in the calculus of variations.

Congestion Control in Data Transmission Networks details the modeling and control of data traffic in communication networks.

Stochastic Averaging and Extremum Seeking treats methods inspired by attempts to understand the seemingly non-mathematical question of bacterial chemotaxis and their application in other environments.

An extended survey of methods for the control and systems identification in gas turbines, this book reviews current methods and presents a number of new perspectives.

H-infinity control theory deals with the minimization of the H-infinity-norm of the transfer matrix from an exogenous disturbance to a pertinent controlled output of a given plant.

This work is aimed at mathematics and engineering graduate students and researchers in the areas of optimization, dynamical systems, control sys- tems, signal processing, and linear algebra.

Distributed Decision Making and Control is a mathematical treatment of relevant problems in distributed control, decision and multiagent systems, The research reported was prompted by the recent rapid development in large-scale networked and embedded systems and communications.