Non-Linear Predictive Control - Theory and Practice

This book collates the important results which have emerged in the field of non-linear model based predictive control. Feedback linearisation, differential flatness, control Lyapunov functions, output feedback and neural networks are all discussed.

Sommario

• Part I


• Chapter 1: Review of nonlinear model predictive control applications


• Chapter 2: Nonlinear model predictive control: issues and applications


• Part II


• Chapter 3: Model predictive control: output feedback and tracking of nonlinear systems


• Chapter 4: Model predictive control of nonlinear parameter varying systems via receding horizon control Lyapunov functions


• Chapter 5: Nonlinear model-algorithmic control for multivariable nonminimum-phase processes


• Part III


• Chapter 6: Open-loop and closed-loop optimality in interpolation MPC


• Chapter 7: Closed-loop predictions in model based predictive control linear and nonlinear systems


• Chapter 8: Computationally efficient non linear predictive control algorithm for control of constrained nonlinear systems


• Part IV


• Chapter 9: Long-prediction-horizon nonlinear model predictive control


• Chapter 10: Nonlinear control of industrial processes


• Chapter 11: Nonlinear model based predictive control using multiple local models


• Chapter 12: Neural network control of a gasoline engine with rapid sampling

Dettagli sul prodotto

• Con la collaborazione di: Mark Cannon (Editore), Basil Kouvaritakis (Editore)
• Editore: Institution of Engineering & Technology
• Lingue: Inglese
• Formato: Copertina rigida
• Pubblicazione: 26.10.2001
• EAN: 9780852969847
• ISBN: 978-0-85296-984-7
• Pagine: 276
• Dimensioni: 155 mm x 239 mm x 18 mm
• Peso: 499 g
• Serie: Iee Control Engineering; Control, Robotics and Sensors; Iee Control Engineering
• Categoria: Scienze naturali, medicina, informatica, tecnica > Tecnica > Meccanica, tecnica di produzione