Provides valuable insights into the use of test-signal design in system identification Helps the reader to make well-informed choices of signal design for process and communications industries Discusses software packages for designing common classes of signals

Autorentext
Ai Hui Tan is an Associate Professor at the Faculty of Engineering, Multimedia University, Cyberjaya, Malaysia. She graduated with first class honours in Electronic Engineering from the University of Warwick, U.K. in 1999. She was awarded a Ph.D. in 2002 for research done in the Systems Modelling and Simulation Research Group at the University of Warwick under the supervision of Professor Keith Godfrey. Her research focusses on several aspects of system identification, including perturbation signal design and applications. She is a member of the IFAC Technical Committee on Modelling, Identification and Signal Processing. She was a recipient of IEE Institution Prize 1999.
**Keith Godfrey** is an Emeritus Professor in the School of Engineering at the University of Warwick. He has been involved in many applications of system identification, and in 1990, he received the Doctor of Science degree from the University of Warwick for publications with the collective title "Applications of Modelling, Identification and Parameter Estimation in Engineering and Biomedicine". He is author, or co-author, of more than 200 papers and is a member of the IFAC Technical Committees on Biomedical Engineering and Control, and on Modelling, Identification and Signal Processing. He has been presented with several international awards for his work.

Zusammenfassung

Industrial Process Identification brings together the latest advances in perturbation signal design. It describes the approaches to the design process that are relevant to industries. The authors' discussion of several software packages (Frequency Domain System Identification Toolbox, prs, GALOIS, multilev_new, and Input-Signal-Creator) will allow readers to understand the different designs in industries and begin designing common classes of signals.

The authors include two case studies that provide a balance between the theory and practice of these designs:

• the identification of a direction-dependent electronic nose system; and

• the identification of a multivariable cooling system with time-varying delay. Major aspects of signal design such as the formulation of suitable specifications in the face of practical constraints, the classes of designs available, the various objectives necessitating separatetreatments when dealing with nonlinear systems, and extension to multi-input scenarios, are discussed. Codes, including some that will produce simulated data, are included to help readers replicate the results described.

Industrial Process Identification is a powerful source of information for control engineers working in the process and communications industries seeking guidance on choosing identification software tools for use in practical experiments and case studies. The book will also be of interest to academic researchers and students working in electrical, mechanical and communications engineering and the application of perturbation signal design.

Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of newwork in all aspects of industrial control.

Inhalt
Introduction.- Design of Pseudo-Random Signals for Linear System Identification.- Design of Computer-Optimized Signals for Linear System Identification.- Signal Design for Multi-input System Identification.- Signal Design for the Identification of Nonlinear and Time-Varying Systems.- Case Study on the Identification of Direction-Dependent Electronic NoseSystem.- Case Study on the Identification of a Multivariable Cooling System with Time-Varying Delay.- Software for Signal Design.