Adaptive Prediction and Predictive Control

by Partha Pratim Kanjilal

Overview

Control often follows predictions: predictive control has been highly successful in producing robust and practical solutions in many real-life, real-time applications. Adaptive prediction covers a variety of ways of adding 'intelligence' to predictive control techniques. Many different groups, with widely varying disciplinary backgrounds and approaches, are tackling the same problem from different angles; these groups are sometimes unaware of alternative approaches from other disciplines.

This book attempts to give a unified and comprehensive coverage of the principles and methods that these groups have developed. It avoids basing its descriptions on very complex mathematical formulations but still gives a rigorous exposure to the subject, and illustrates the theory with many practical examples. It is chiefly aimed at students, researchers and practitioners, but will also be accessible to the non-specialist.

Product Details

ISBN-13:	9780863411939
Publisher:	The Institution of Engineering and Technology
Publication date:	06/30/1995
Series:	Control, Robotics and Sensors
Pages:	536
Product dimensions:	6.14(w) x 9.21(h) x (d)

About the Author

Partha Pratim Kanjilal is an Associate Professor at the Indian Institute of Technology, Kharagpur. He is a graduate of the IIT and of the Universityof Sheffield. His research interests include modelling and prediction of complex processes, linear and nonlinear time-series analysis, signal processing and predictive control. He has a particular interest in the applications of orthogonal control. Dr Kanjilal has previously worked as a research fellow at Oxford University, CSIR and Tata Steel in India. He has published over 25 refereed papers in journals and international conferences.

Table of Contents

• Chapter 1: Introduction
• Chapter 2: Process models
• Chapter 3: Parameter estimation
• Chapter 4: Some popular methods of prediction
• Chapter 5: Adaptive prediction using transfer-function models
• Chapter 6: Kalman filter and state-space approaches
• Chapter 7: Orthogonal transformation and modelling of periodic series
• Chapter 8: Modellong of nonlinear processes: an introduction
• Chapter 9: Modelling of nonlinear processes using GMDH
• Chapter 10: Modelling and prediction of nonlinear processes using neural networks
• Chapter 11: Modelling and prediction of quasiperiodic series
• Chapter 12: Predictive control (Part-I): input-output model based
• Chapter 13: Predictive control (Part-II): state-space model based
• Chapter 14: Smoothing and filtering
• Appendices

Editorial Reviews

'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

Provides unified coverage of the principles and methods of various disciplines' approaches to prediction and control of processes expressed by discrete-time models, especially adaptive prediction, for students, researchers, and practitioners in the field. Chapters on methods of adaptive prediction for linear and non-linear processes, such as input-output model based prediction and Kalman filter predictors, avoid complex mathematical symbols and expressions, and contain examples and case studies. Includes introductory material on process models and parameter estimation, plus reference appendices and data sets. Annotation c. Book News, Inc., Portland, OR (booknews.com)

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