Numerical Methods For Optimal Control Problems
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Numerical Methods for Optimal Control Problems with State Constraints
Author: Radoslaw Pytlak
language: en
Publisher: Springer Science & Business Media
Release Date: 1999-08-19
While optimality conditions for optimal control problems with state constraints have been extensively investigated in the literature the results pertaining to numerical methods are relatively scarce. This book fills the gap by providing a family of new methods. Among others, a novel convergence analysis of optimal control algorithms is introduced. The analysis refers to the topology of relaxed controls only to a limited degree and makes little use of Lagrange multipliers corresponding to state constraints. This approach enables the author to provide global convergence analysis of first order and superlinearly convergent second order methods. Further, the implementation aspects of the methods developed in the book are presented and discussed. The results concerning ordinary differential equations are then extended to control problems described by differential-algebraic equations in a comprehensive way for the first time in the literature.
Numerical Methods for Stochastic Control Problems in Continuous Time
Author: Harold J. Kushner
language: en
Publisher: Springer Science & Business Media
Release Date: 2001
The required background is surveyed, and there is an extensive development of methods of approximation and computational algorithms. The book is written on two levels: algorithms and applications, and mathematical proofs. Thus, the ideas should be very accessible to a broad audience."--BOOK JACKET.
Practical Methods for Optimal Control and Estimation Using Nonlinear Programming
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.