DISCRETE-TIME CONTROL ALGORITHMS DESIGN

In this book, approximate dynamic programming (ADP) designs based on adaptive critic structures are developed to solve the discrete-time optimal control problems in which the state and action spaces are continuous. This work considers linear discrete-time systems as well as nonlinear discrete- time systems that are affine in the input. This work resulted in forward-in-time reinforcement learning algorithms that converge to the solution of the Generalized Algebraic Riccati Equation (GARE) for linear systems. For the nonlinear case, a forward-in-time reinforcement learning algorithm is presented that converges to the solution of the associated Hamilton-Jacobi Bellman equation (HJB).

Autorentext

A. AL-Tamimi is with Hashemite University,Zarqa 13115,Jordan (e-mail: altamimi@hu.edu.jo). F. L. Lewis is with the Automation and Robotics Research Institute, The University of Texas at Arlington, Fort Worth, TX 76118 USA (e-mail: lewis@uta.edu). M. Abu-Khalaf is with The MathWorks, Inc., Natick, MA 01760 USA ( email Murad.Abu-Khalaf@mathworks.com.