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Adaptive Prediction and ­Predictive Control
Control, Robotics and Sensors

Rating
Format
Hardback, 536 pages
Published
United Kingdom, 1 June 1995

This monograph is concerned with the prediction and control of processes expressed by discrete-time models. It is assumed that the characteristics of the process may vary over time. The processes concerned may be linear or nonlinear, periodic or nonperiodic, single input/single output or simply output-only time series. The primary aim of the work is to provide comprehensive coverage of the principles, perspectives and methods of adaptive prediction. There is also an introduction to the popular methods of predictive control. The numerical and computational aspects of prediction and control methods often influence their success in operation, and for this reason the text gives them due consideration whenever possible.


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Product Description

This monograph is concerned with the prediction and control of processes expressed by discrete-time models. It is assumed that the characteristics of the process may vary over time. The processes concerned may be linear or nonlinear, periodic or nonperiodic, single input/single output or simply output-only time series. The primary aim of the work is to provide comprehensive coverage of the principles, perspectives and methods of adaptive prediction. There is also an introduction to the popular methods of predictive control. The numerical and computational aspects of prediction and control methods often influence their success in operation, and for this reason the text gives them due consideration whenever possible.

Product Details
EAN
9780863411939
ISBN
0863411932
Dimensions
23.4 x 15.6 x 3 centimeters (0.93 kg)

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

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 University of 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.

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*

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