Dynamic optimization, Volume 1

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Addison Wesley Longman, 1999 - Computers - 434 pages
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"Dynamic Optimization" takes an applied approach to its subject, offering many examples and solved problems that draw from aerospace, robotics, and mechanics. The abundance of thoroughly tested general algorithms and Matlab codes provide the reader with the practice necessary to master this inherently difficult subject, while the realistic engineering problems and examples keep the material interesting and relevant.

FEATURES/BENEFITS

  • Covers dynamic programming, relating it to the calculus of variations and optimal control, and neighboring optimum control (differential dynamic programming), a practical method for nonlinear feedback control.
  • Includes a disk that contains 40 gradient and shooting codes, as well as codes that solve the time-varying Riccati equation (the DYNOPT Toolbox). These codes have been thoroughly tested on hundreds of problems.
  • Contains many realistic examples and problems. Solutions to the examples and problems, as well as the codes that produce the figures, are included on the accompanying disk.
  • Covers dynamic optimization with inequality constraints and singular arcs using inverse dynamic optimization (differential inclusion).

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Contents

1 POPParameter Optimization Using Gradient
30
2 POPNParameter Optimization Using NR
41
Dynamic Optimization
45
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sciencedirect - Automatica : Dynamic optimization Arthur E. Bryson ...
The field of Dynamic Optimization, or Optimal Control as it is more frequently called, dates from the late 1950s. It emerged in response to new kinds of ...
linkinghub.elsevier.com/ retrieve/ pii/ S0005109802000845

[Paper] Dynamic Optimization using Hermite Chaos
DYNAMIC OPTIMIZATION USING HERMITE CHAOS Franz S. Hover Department of Mechanical Engineering Massachusetts Institute of Technology 77 Massachusetts Avenue ...
www.actapress.com/ PDFViewer.aspx?paperId=19654

MATLAB Central File Exchange - Dynamic Optimization
Description: This book starts with a review of parameter optimization and then treats dynamic optimization, first with fixed final time and no constraints, ...
www.mathworks.com/ matlabcentral/ fileexchange/ loadFile.do?objectId=2429& objectType=File

OBJECT LIBRARY OF ALGORITHMS FOR DYNAMIC OPTIMIZATION PROBLEMS ...
dynamic optimization problems, and give a general survey of solver classes for ... dynamic optimization are presented in detail: the sequential quadratic ...
matwbn.icm.edu.pl/ ksiazki/ amc/ amc17/ amc1749.pdf

Neighbouring extremals of dynamic optimization problems with ...
Neighbouring extremals of dynamic optimization problems with a known parameter vector 8 and an. unknown parameter vector. T. are considered in this paper. ...
doi.wiley.com/ 10.1002/ oca.4660100104

Dynamic Optimization of Startup and Load-Increasing Processes in ...
The fast startup and load-increasing process of power plants is a complex task involving several restrictions that have to be fulfilled simultaneously
link.aip.org/ link/ ?JETPEZ/ 123/ 246/ 1

Dynamic optimization in business-wide process control
7.2 The sequential approach for dynamic optimization . . . . . . . . 129 ...... the Delft University of Technology into the dynamic optimization and control ...
www.dcsc.tudelft.nl/ Research/ PublicationFiles/ publication-5746.pdf

Neural dynamic optimization for control systems-Part I: background ...
Abstract—The paper presents neural dynamic optimization ... shift operator, learning operator, neural dynamic optimization ...
ieeexplore.ieee.org/ iel5/ 3477/ 20310/ 00938254.pdf?arnumber=938254

Brief paper
Brief paper: Gradient dynamic optimization with Legendre chaos ... Stochastic dynamic optimization of batch and semicontinuous bioprocesses. ...
portal.acm.org/ citation.cfm?id=1330766.1330869& coll=GUIDE& dl=& CFID=15151515& CFTOKEN=6184618

Dynamic Optimization of Batch Processes: II. Handling Uncertainty ...
Possible scenarios in dynamic optimization are depicted ...... The dynamic optimization problem considered in (1)-(3) has two types of constraints: i) the ...
infoscience.epfl.ch/ record/ 28407/ files/ fulltext.pdf

About the author (1999)

Arthur E. Bryson is Pigott Professor of Engineering Emeritus at Stanford University, where he served on the faculty from 1968 to 1994. He has also taught at Harvard and MIT and worked as a research engineer and consultant at Hughes Aircraft and Raytheon. Professor Bryson is a member of the National Academy of Engineering and the National Academy of Sciences. His awards include the IEEE Control Systems Award, the ASME Oldenberger Award, and the AACC Bellman Award. He is an Honorary Fellow of AIAA and an Honorary Member of IEEE. He is the author of 100 papers and three books.

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