Control Oriented System Identification: An H∞ Approach - Hardcover

Chen, Jie; Gu, Guoxiang

Hardcover

ISBN 10: 047132048X ISBN 13: 9780471320487

Publisher: Wiley-Interscience, 2000

Synopsis

Model-based fault detection and isolation requires a mathematical model of the system behaviour. Modelling is important and can be difficult because of the complexity of the monitored system and its control architecture. The authors use bond-graph modelling, a unified multi-energy domain modelling method, to build dynamic models of process engineering systems by composing hierarchically arranged sub-models of various commonly encountered process engineering devices. The structural and causal properties of bond-graph models are exploited for supervisory systems design. The structural properties of a system, necessary for process control, are elegantly derived from bond-graph models by following the simple algorithms presented here. Additionally, structural analysis of the model augmented with available instrumentation indicates directly whether it is possible to detect and/or isolate faults in some specific sub-space of the process. Such analysis aids in the design and resource optimiza

About this title

From the Back Cover

A comprehensive, one-stop reference for new system modeling and identification tools

The field of control-oriented identification has grown immensely over the past decade, spawning numerous results and modeling techniques and promising the potential to influence science and engineering for years to come. In this new work, Jie Chen and Guoxiang Gu, two leading authorities on worst-case identification, share their vision and walk readers through carefully selected topics from the vast literature, offering a much-needed, timely comprehensive introduction to the theory of H? identification and model validation.

Chen and Gu clearly demonstrate the pros and cons of the worst-case approach in comparison to traditional techniques and provide researchers in systems and control theory with ready access to many new and complementary identification tools. Through a rigorous yet logical and easy-to-follow treatment, supported by many deep insights, intuitions, and philosophical thinking, they:

• Survey and assess the current state of control and system identification research
• Develop both two-stage and interpolatory algorithms for system identification
• Show readers how to analyze the properties of linear algorithms
• Offer a unique emphasis on model uncertainty estimation and complexity, two of the central issues
• Develop both time-domain and frequency-domain identification algorithms
• Explain in detail uncertainty model validation concepts and techniques
• Devote a chapter to a review of the requisite mathematics

Provide a concise yet self-contained appendix on several key relevant notions

About the Author

JIE CHEN, PhD, is Professor of Electrical Engineering at the University of California, Riverside. GUOXIANG GU, PhD, is Professor in the Department of Electrical and Computer Engineering at Louisiana State University, Baton Rouge.

Edition details

• Publisher: Wiley-Interscience
• Publication date: 2000
• ISBN 10: 047132048X
• ISBN 13: 9780471320487
• Binding: Hardcover
• Language: English
• Edition number: 1
• Number of pages: 440