Optimal Control Theory

Optimal Control Theory

Author: Suresh P. Sethi

Publisher: Springer Nature

Published: 2022-01-03

Total Pages: 520

ISBN-13: 3030917452

DOWNLOAD EBOOK

This new 4th edition offers an introduction to optimal control theory and its diverse applications in management science and economics. It introduces students to the concept of the maximum principle in continuous (as well as discrete) time by combining dynamic programming and Kuhn-Tucker theory. While some mathematical background is needed, the emphasis of the book is not on mathematical rigor, but on modeling realistic situations encountered in business and economics. It applies optimal control theory to the functional areas of management including finance, production and marketing, as well as the economics of growth and of natural resources. In addition, it features material on stochastic Nash and Stackelberg differential games and an adverse selection model in the principal-agent framework. Exercises are included in each chapter, while the answers to selected exercises help deepen readers’ understanding of the material covered. Also included are appendices of supplementary material on the solution of differential equations, the calculus of variations and its ties to the maximum principle, and special topics including the Kalman filter, certainty equivalence, singular control, a global saddle point theorem, Sethi-Skiba points, and distributed parameter systems. Optimal control methods are used to determine optimal ways to control a dynamic system. The theoretical work in this field serves as the foundation for the book, in which the author applies it to business management problems developed from his own research and classroom instruction. The new edition has been refined and updated, making it a valuable resource for graduate courses on applied optimal control theory, but also for financial and industrial engineers, economists, and operational researchers interested in applying dynamic optimization in their fields.


Hybrid Systems, Optimal Control and Hybrid Vehicles

Hybrid Systems, Optimal Control and Hybrid Vehicles

Author: Thomas J. Böhme

Publisher: Springer

Published: 2017-02-01

Total Pages: 549

ISBN-13: 3319513176

DOWNLOAD EBOOK

This book assembles new methods showing the automotive engineer for the first time how hybrid vehicle configurations can be modeled as systems with discrete and continuous controls. These hybrid systems describe naturally and compactly the networks of embedded systems which use elements such as integrators, hysteresis, state-machines and logical rules to describe the evolution of continuous and discrete dynamics and arise inevitably when modeling hybrid electric vehicles. They can throw light on systems which may otherwise be too complex or recondite. Hybrid Systems, Optimal Control and Hybrid Vehicles shows the reader how to formulate and solve control problems which satisfy multiple objectives which may be arbitrary and complex with contradictory influences on fuel consumption, emissions and drivability. The text introduces industrial engineers, postgraduates and researchers to the theory of hybrid optimal control problems. A series of novel algorithmic developments provides tools for solving engineering problems of growing complexity in the field of hybrid vehicles. Important topics of real relevance rarely found in text books and research publications—switching costs, sensitivity of discrete decisions and there impact on fuel savings, etc.—are discussed and supported with practical applications. These demonstrate the contribution of optimal hybrid control in predictive energy management, advanced powertrain calibration, and the optimization of vehicle configuration with respect to fuel economy, lowest emissions and smoothest drivability. Numerical issues such as computing resources, simplifications and stability are treated to enable readers to assess such complex systems. To help industrial engineers and managers with project decision-making, solutions for many important problems in hybrid vehicle control are provided in terms of requirements, benefits and risks.


Computational Optimal Control

Computational Optimal Control

Author: Dr Subchan Subchan

Publisher: John Wiley & Sons

Published: 2009-08-19

Total Pages: 202

ISBN-13: 0470747684

DOWNLOAD EBOOK

Computational Optimal Control: Tools and Practice provides a detailed guide to informed use of computational optimal control in advanced engineering practice, addressing the need for a better understanding of the practical application of optimal control using computational techniques. Throughout the text the authors employ an advanced aeronautical case study to provide a practical, real-life setting for optimal control theory. This case study focuses on an advanced, real-world problem known as the “terminal bunt manoeuvre” or special trajectory shaping of a cruise missile. Representing the many problems involved in flight dynamics, practical control and flight path constraints, this case study offers an excellent illustration of advanced engineering practice using optimal solutions. The book describes in practical detail the real and tested optimal control software, examining the advantages and limitations of the technology. Featuring tutorial insights into computational optimal formulations and an advanced case-study approach to the topic, Computational Optimal Control: Tools and Practice provides an essential handbook for practising engineers and academics interested in practical optimal solutions in engineering. Focuses on an advanced, real-world aeronautical case study examining optimisation of the bunt manoeuvre Covers DIRCOL, NUDOCCCS, PROMIS and SOCS (under the GESOP environment), and BNDSCO Explains how to configure and optimize software to solve complex real-world computational optimal control problems Presents a tutorial three-stage hybrid approach to solving optimal control problem formulations


The Sequential Quadratic Hamiltonian Method

The Sequential Quadratic Hamiltonian Method

Author: Alfio Borzì

Publisher: CRC Press

Published: 2023-05-26

Total Pages: 267

ISBN-13: 1000882462

DOWNLOAD EBOOK

The sequential quadratic hamiltonian (SQH) method is a novel numerical optimization procedure for solving optimal control problems governed by differential models. It is based on the characterisation of optimal controls in the framework of the Pontryagin maximum principle (PMP). The SQH method is a powerful computational methodology that is capable of development in many directions. The Sequential Quadratic Hamiltonian Method: Solving Optimal Control Problems discusses its analysis and use in solving nonsmooth ODE control problems, relaxed ODE control problems, stochastic control problems, mixed-integer control problems, PDE control problems, inverse PDE problems, differential Nash game problems, and problems related to residual neural networks. This book may serve as a textbook for undergraduate and graduate students, and as an introduction for researchers in sciences and engineering who intend to further develop the SQH method or wish to use it as a numerical tool for solving challenging optimal control problems and for investigating the Pontryagin maximum principle on new optimisation problems. Features Provides insight into mathematical and computational issues concerning optimal control problems, while discussing many differential models of interest in different disciplines. Suitable for undergraduate and graduate students and as an introduction for researchers in sciences and engineering. Accompanied by codes which allow the reader to apply the SQH method to solve many different optimal control and optimisation problems.


System Modeling and Optimization

System Modeling and Optimization

Author: Adam Korytowski

Publisher: Springer

Published: 2009-10-27

Total Pages: 515

ISBN-13: 3642048021

DOWNLOAD EBOOK

rd This book constitutes a collection of extended versions of papers presented at the 23 IFIP TC7 Conference on System Modeling and Optimization, which was held in C- cow, Poland, on July 23–27, 2007. It contains 7 plenary and 22 contributed articles, the latter selected via a peer reviewing process. Most of the papers are concerned with optimization and optimal control. Some of them deal with practical issues, e. g. , p- formance-based design for seismic risk reduction, or evolutionary optimization in structural engineering. Many contributions concern optimization of infini- dimensional systems, ranging from a general overview of the variational analysis, through optimization and sensitivity analysis of PDE systems, to optimal control of neutral systems. A significant group of papers is devoted to shape analysis and opti- zation. Sufficient optimality conditions for ODE problems, and stochastic control methods applied to mathematical finance, are also investigated. The remaining papers are on mathematical programming, modeling, and information technology. The conference was the 23rd event in the series of such meetings biennially org- ized under the auspices of the Seventh Technical Committee “Systems Modeling and Optimization” of the International Federation for Information Processing (IFIP TC7).


Designing Robot Behavior in Human-Robot Interactions

Designing Robot Behavior in Human-Robot Interactions

Author: Changliu Liu

Publisher: CRC Press

Published: 2019-09-12

Total Pages: 217

ISBN-13: 0429602855

DOWNLOAD EBOOK

In this book, we have set up a unified analytical framework for various human-robot systems, which involve peer-peer interactions (either space-sharing or time-sharing) or hierarchical interactions. A methodology in designing the robot behavior through control, planning, decision and learning is proposed. In particular, the following topics are discussed in-depth: safety during human-robot interactions, efficiency in real-time robot motion planning, imitation of human behaviors from demonstration, dexterity of robots to adapt to different environments and tasks, cooperation among robots and humans with conflict resolution. These methods are applied in various scenarios, such as human-robot collaborative assembly, robot skill learning from human demonstration, interaction between autonomous and human-driven vehicles, etc. Key Features: Proposes a unified framework to model and analyze human-robot interactions under different modes of interactions. Systematically discusses the control, decision and learning algorithms to enable robots to interact safely with humans in a variety of applications. Presents numerous experimental studies with both industrial collaborative robot arms and autonomous vehicles.


Optimal Measurement Methods for Distributed Parameter System Identification

Optimal Measurement Methods for Distributed Parameter System Identification

Author: Dariusz Ucinski

Publisher: CRC Press

Published: 2004-08-27

Total Pages: 390

ISBN-13: 0203026780

DOWNLOAD EBOOK

For dynamic distributed systems modeled by partial differential equations, existing methods of sensor location in parameter estimation experiments are either limited to one-dimensional spatial domains or require large investments in software systems. With the expense of scanning and moving sensors, optimal placement presents a critical problem.


Online Optimization of Large Scale Systems

Online Optimization of Large Scale Systems

Author: Martin Grötschel

Publisher: Springer Science & Business Media

Published: 2013-03-14

Total Pages: 789

ISBN-13: 3662043319

DOWNLOAD EBOOK

In its thousands of years of history, mathematics has made an extraordinary ca reer. It started from rules for bookkeeping and computation of areas to become the language of science. Its potential for decision support was fully recognized in the twentieth century only, vitally aided by the evolution of computing and communi cation technology. Mathematical optimization, in particular, has developed into a powerful machinery to help planners. Whether costs are to be reduced, profits to be maximized, or scarce resources to be used wisely, optimization methods are available to guide decision making. Opti mization is particularly strong if precise models of real phenomena and data of high quality are at hand - often yielding reliable automated control and decision proce dures. But what, if the models are soft and not all data are around? Can mathematics help as well? This book addresses such issues, e. g. , problems of the following type: - An elevator cannot know all transportation requests in advance. In which order should it serve the passengers? - Wing profiles of aircrafts influence the fuel consumption. Is it possible to con tinuously adapt the shape of a wing during the flight under rapidly changing conditions? - Robots are designed to accomplish specific tasks as efficiently as possible. But what if a robot navigates in an unknown environment? - Energy demand changes quickly and is not easily predictable over time. Some types of power plants can only react slowly.


Multi-agent Optimization

Multi-agent Optimization

Author: Angelia Nedić

Publisher: Springer

Published: 2018-11-01

Total Pages: 317

ISBN-13: 3319971425

DOWNLOAD EBOOK

This book contains three well-written research tutorials that inform the graduate reader about the forefront of current research in multi-agent optimization. These tutorials cover topics that have not yet found their way in standard books and offer the reader the unique opportunity to be guided by major researchers in the respective fields. Multi-agent optimization, lying at the intersection of classical optimization, game theory, and variational inequality theory, is at the forefront of modern optimization and has recently undergone a dramatic development. It seems timely to provide an overview that describes in detail ongoing research and important trends. This book concentrates on Distributed Optimization over Networks; Differential Variational Inequalities; and Advanced Decomposition Algorithms for Multi-agent Systems. This book will appeal to both mathematicians and mathematically oriented engineers and will be the source of inspiration for PhD students and researchers.