Ch. 1. Introduction -- ch. 2. Mathematical preliminaries -- ch. 3. Inverse optimal control : a passivity approach -- ch. 4. Inverse optimal control : a CLF approach, part I -- ch. 5. Inverse optimal control : a CLF approach, part II -- ch. 6. Neural inverse optimal control -- ch. 7. Glycemic control of type 1 diabetes mellitus patients -- ch. 8. Conclusions
Summary
"This book presents a novel inverse optimal control approach for stabilization and trajectory tracking of discrete-time nonlinear systems, avoiding the need to solve the associated Hamilton-Jacobi-Bellman equation, and minimizing a cost functional, resulting in efficient controllers. Additionally, the book proposes the use of recurrent neural networks as a tool to model discrete-time nonlinear systems; such models combined with the inverse optimal control constitute a powerful tool to deal with uncertainties such as unmodeled dynamics and disturbances. Different simulations illustrate the effectiveness of the synthesized controllers for stabilization and trajectory tracking of discrete-time nonlinear systems"-- Provided by publisher
Bibliography
Includes bibliographical references (pages 203-219) and index
