Description

 

Scope: This book is about prediction and control of processes which can be expressed by discrete-time models (i.e. the characteristics vary in some way with time). The aim of the book is to provide a unified and comprehensive coverage of the principles, perspectives and methods of adaptive prediction, which is used by scientists and researchers in a wide variety of disciplines. Control often follows prediction. Within the adaptive control field, the ability to be predictive is useful in many real-life situations. The book introduces popular methods of predictive control.

Book review

"The book contains useful new material that can support postgraduate courses in the fields of control and signal processing. It can serve researchers and practicing engineers as a useful reference. On the whole, [the] book is an important contribution to the literature on the subject." IEEE Transactions on Automatic Control

Book readership

Electrical / control / systems engineers.

Book contents

Introduction; Process models; Parameter estimation; Some popular methods of prediction; Adaptive prediction using transfer function models; Kalman filter and state-space approaches; Orthogonal transformation and modelling of periodic series; Modelling of non-linear processes using GMDH; Modelling and prediction of non-linear processes using neural networks; Modelling and prediction of quasiperiodic series; Predictive control I - input-output model based; Predictive control II - state-space model based; Smoothing and filtering; Appendices; Index.



Powered by Google
Search the full text of this book