Practical Methods for Optimal Control and Estimation Using Nonlinear Programming
This second edition of the popular text by John Betts incorporates lots of new material while maintaining the concise and focused presentation of the original edition. The book describes how sparse optimization methods can be combined with discretization techniques for differential-algebraic equations and used to solve optimal control and estimation problems. The interaction between optimization and integration is emphasized throughout the book. The relevant background in nonlinear programming methods that exploit sparse matrix technology is presented, along with description of discretization techniques for solving differential-algebraic equations. It will appeal to users of optimal control working in fields such as the aerospace industry, chemical process control, mathematical biology, robotics and multibody simulation, and engineering. It is also suitable for graduate courses on optimal control methods. The SOCS software referenced within the book can be licensed from Boeing by readers interested in receiving the code and training materials for further investigation.
- A concise guide for anyone who uses optimal control
- Introduces all the basic material needed to solve an optimal control problem
- Contains an extensive collection of example problems in order to demonstrate the methods
Product details
December 2009Hardback
9780898716887
458 pages
262 × 182 × 25 mm
0.95kg
This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
Table of Contents
- Preface
- 1. Introduction to nonlinear programming
- 2. Large, sparse nonlinear programming
- 3. Optimal control preliminaries
- 4. The optimal control problem
- 5. Parameter estimation
- 6. Optimal control examples
- 7. Advanced applications
- 8. Epilogue
- Appendix. Software
- Bibliography
- Index.