Model based predictive control has proved to be a fertile area of research, but above all has gained enormous success with industry, especially in the context of process control. Non-linear model based predictive control is of particular interest as this best represents the dynamics of most real plants, and this book collects together the important results which have emerged in this field which are illustrated by means of simulations on industrial models. In particular there are contributions on feedback linearization, differential flatness, control Lyapunov functions, output feedback, and neural networks. The international contributors to the book are all respected leaders within the field, which makes for essential reading for advanced students, researchers and industrialists in the field of control of complex systems.
Author(s): Basil Kouvaritakis (editor), Mark Cannon (editor)
Series: Control Engineering Series 61
Edition: 1
Publisher: IET
Year: 2001
Language: English
Pages: 272
Contents......Page 6
Preface......Page 12
Contirbutors......Page 14
Part I......Page 16
1. Review of nonlinear model predictive control application......Page 18
2. Nonlinear model predictive control: issues and applications......Page 48
Part II......Page 74
3. Model predictive control: output feedback and tracking of nonlinear systems......Page 76
4. Model predictive control of nonlinear parameter varying systems via recoding horizon control Lyapunov funcions......Page 96
5. Nonlinear model-algorithmic control for multivariable nonminimum-phase process......Page 122
6. Open-loop and closed-loop optimality in interpolation MPC......Page 146
Part III......Page 166
7. Closed-loop preditions in model based predictive control of linear and nonlinear systems......Page 168
8. Computationally efficient nonlinear predictive control algorithm for control of constrained non-linear systems......Page 188
9. Long-prediction-horizon nonlinear model predictive control......Page 204
Part IV......Page 218
10. Nonlinear control of industrial processes......Page 220
11. Nonlinear model based predictive control using multiple local models......Page 238
12. Neural network control of a gasoline engine with rapid sampling......Page 260
Index......Page 272
