Dynamic Optimization

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 student with the practice necessary to master this inherently difficult subject, while the realistic engineering problems and examples keep the material interesting and relevant.

Table of Contents:
1. Static Optimization. Problems without Constraints. Problems with Equality Constraints. Numerical Solution with Gradient Methods. Sufficient Conditions for a Minimum. Numerical Solution with Newton-Raphson Methods. Chapter Summary. 2. Dynamic Optimization. Discrete Dynamic Systems. Numerical Solution with Gradient Methods. Continuous Dynamic Systems. Numerical Solution with Gradient Methods. Direct Solution Methods for Discrete Systems. Direct Solution Methods for Continuous Systems. Chapter Summary. 3. Dynamic Optimization with Terminal Constraints. Discrete Dynamic Systems. Numerical Solution with Gradient Methods. Continuous Dynamic Systems. Numerical Solution with Gradient Methods. Direct Solution Methods for Discrete Systems. Direct Solution Methods for Continuous Systems. Chapter Summary. 4. Dynamic Optimization with Open Final Time. Discrete Dynamic Systems. Numerical Solution with Gradient Methods. Continuous Dynamic Systems. Numerical Solution with Gradient Methods. Direct Solution Methods for Discrete Systems. Direct Solution Methods for Continuous Systems. Chapter Summary. 5. Linear-Quadratic Terminal Controllers. Introduction. Continuous Soft Terminal Controllers. Discrete Soft Terminal Controllers. Continuous Hard Terminal Controllers. Discrete Hard Terminal Controllers. Chapter Summary. 6. Linear-Quadratic Regulators. Introduction. Continuous Regulators. Discrete Regulators. Chapter Summary. 7. Dynamic Programming. Introduction. Extremal Fields. The Continuous Minimum Principle. The Combinatorial Minimum Principle. Chapter Summary. 8. Neighboring Optimum Feedback Control. Introduction. The Accessory Minimum Problem for Continuous Systems. The Accessory Minimum Problem for Discrete Systems. A Newton-Raphson Algorithm for Discrete Systems. Sufficient Conditions and Convexity. Nonconvex Terminal Manifolds - Focal Points. Nonconvex Space - Conjugate Points. Chapter Summary. 9. Inequality Constraints. Introduction. Static Optimization. Dynamic Optimization. Chapter Summary. 10. Singular Optimal Control Problems. Introduction. LQ Controllers for Nonminimum Phase Systems. Nonlinear Problems with Singular Arcs. Chapter Summary. Appendix: History of Dynamic Optmization. References. Index.

About the Author :
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.