Practical Methods for Optimal Control Using Nonlinear Programming, Third Edition [Bookshelf]

Optimal control is a subject that dates back nearly 100 years. The roots of optimal control lie in the subject of variational calculus, which was originally invented by Leonhard Euler (1707-1783). Fundamentally, an optimal control problem is one where it is desired to determine the state and control...

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Published inIEEE control systems Vol. 43; no. 4; pp. 94 - 95
Main Author Rao, Anil V.
Format Book Review Magazine Article
LanguageEnglish
Published New York IEEE 01.08.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Online AccessGet full text
ISSN1066-033X
1941-000X
1941-000X
DOI10.1109/MCS.2023.3273823

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Abstract Optimal control is a subject that dates back nearly 100 years. The roots of optimal control lie in the subject of variational calculus, which was originally invented by Leonhard Euler (1707-1783). Fundamentally, an optimal control problem is one where it is desired to determine the state and control of a controlled dynamical system while optimizing (minimizing or maximizing) a performance index (generally referred to as an objective functional ) that is subject to additional constraints such as boundary conditions, interior-point constraints, and path constraints. Such a problem, stated so succinctly, can also be formulated mathematically in a deceivingly simple manner. Because of the seeming simplicity of both the problem statement and the problem formulation, one might conclude that solving an optimal control problem is an easy task. To the contrary, obtaining the solution to a (generally nonlinear) optimal control problem is by no means a simple process. The author states this last point quite elegantly in the very first sentence of the preface of the book: "Solving an optimal control problem is not easy."
AbstractList Optimal control is a subject that dates back nearly 100 years. The roots of optimal control lie in the subject of variational calculus, which was originally invented by Leonhard Euler (1707-1783). Fundamentally, an optimal control problem is one where it is desired to determine the state and control of a controlled dynamical system while optimizing (minimizing or maximizing) a performance index (generally referred to as an objective functional ) that is subject to additional constraints such as boundary conditions, interior-point constraints, and path constraints. Such a problem, stated so succinctly, can also be formulated mathematically in a deceivingly simple manner. Because of the seeming simplicity of both the problem statement and the problem formulation, one might conclude that solving an optimal control problem is an easy task. To the contrary, obtaining the solution to a (generally nonlinear) optimal control problem is by no means a simple process. The author states this last point quite elegantly in the very first sentence of the preface of the book: "Solving an optimal control problem is not easy."
The review of this book is centered on the sheer quality and profoundness with which the author guides a reader through all aspects of solving a general optimal control problem numerically. The basis of the methodology is nonlinear programming, and when traversing the book, the author makes it abundantly clear that optimal control is inextricably bound to nonlinear programming. In fact, the connection the author makes between nonlinear programming and optimal control is so strong that it makes it wholly evident that optimal control problems cannot be solved numerically unless sophisticated techniques for discretizing differential equations (the optimal control side of things) are developed along with equally sophisticated approaches for solving large, sparse, nonlinear programming problems. The book is divided into ten main chapters. It starts off with an introduction to nonlinear programming and then describes large sparse nonlinear programming. From that point, it provides an overview of optimal control. Once that has been accomplished, methods that combine optimal control with nonlinear programming are described, and the main approach of direct collocation is developed in detail. After developing direct collocation methods, the remainder of the book focuses on a large number of amazing examples and ends with a chapter that contains numerous test problems.
Author Rao, Anil V.
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10.1201/9781315137667
10.1145/3390463
10.1109/cacsd.2010.5612676
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References ref8
Bertsekas (ref1) 2016
Ross (ref7) 2020
ref9
ref4
Kirk (ref3) 2004
ref10
Nocedal (ref2) 2006
Athans (ref5) 2006
von Stryk (ref6) 2000
References_xml – volume-title: Nonlinear Programming
  year: 2016
  ident: ref1
– volume-title: Numerical Optimization
  year: 2006
  ident: ref2
– year: 2020
  ident: ref7
  article-title: Enhancements to the DIDO optimal control toolbox
– ident: ref9
  doi: 10.1145/2558904
– ident: ref4
  doi: 10.1201/9781315137667
– volume-title: Optimal Control: An Introduction to the Theory and Its Applications
  year: 2006
  ident: ref5
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  doi: 10.1145/3390463
– ident: ref8
  doi: 10.1109/cacsd.2010.5612676
– volume-title: Optimal Control Theory: An Introduction
  year: 2004
  ident: ref3
– volume-title: Users Guide for DIRCOL (Version 2.1): A Direct Collocation Method for the Numerical Solution of Optimal Control Problems
  year: 2000
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Snippet Optimal control is a subject that dates back nearly 100 years. The roots of optimal control lie in the subject of variational calculus, which was originally...
The review of this book is centered on the sheer quality and profoundness with which the author guides a reader through all aspects of solving a general...
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StartPage 94
SubjectTerms Collocation methods
Differential equations
Nonlinear control
Nonlinear programming
Optimal control
Process control
Programming
Software packages
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Title Practical Methods for Optimal Control Using Nonlinear Programming, Third Edition [Bookshelf]
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