Discrete-time high order neural control: trained with kalman filtering

The objective of this work is to present recent advances in the theory of neural control for discrete-time nonlinear systems with multiple inputs and multiple outputs. The results that appear in each chapter include rigorous mathematical analyses, based on the Lyapunov approach, that guarantee its properties; in addition, for each chapter, simulation results are included to verify the successful performance of the corresponding proposed schemes. In order to complete the treatment of these schemes, the final chapter presents experimental results related to their application to a electric three phase induction motor, which show the applicability of such designs. The proposed schemes could be employed for different applications beyond the ones presented in this book. The book presents solutions for the output trajectory tracking problem of unknown nonlinear systems based on four schemes. Presents recent advances in the theory of neural control for discrete-time nonlinear systems with multiple inputs and multiple outputs INDICE: Introduction.- Mathematical preliminaries.- Discrete Time AdaptiveNeural Backstepping.- Discrete Time Block Control.- Discrete Time Neural Observers.- Discrete Time Output Trajectory Tracking.- Real Time Implementation.- Conclusions and future work.

• ISBN: 978-3-540-78288-9
• Editorial: Springer
• Encuadernacion: Cartoné
• Páginas: 125
• Fecha Publicación: 01/04/2008
• Nº Volúmenes: 1
• Idioma: Inglés