Introduction to System Identification for Control

Author: Zhou Tong
Publisher:
Publish Date: 2004-10-01
Features: Robustness is an important performance index in control system analysis and synthesis. To achieve this performance index, it is required to provide the nominal model of the control object and the error bounds that match robust control theory during the modeling process. In the field of system identification, this problem is known as model set identification. Based on the author's experience and results from over a decade of research on this issue, this book systematically introduces the similarities and differences between robust control modeling and traditional system identification, the connection between model set identification and robust control, as well as the main methods and results in robust control modeling. These methods include model set identification and verification under deterministic frameworks, model set identification and verification under stochastic frameworks, and model set identification and verification based on closed-loop experimental data, among others. The specific content includes fundamental conclusions based on these methods and topics that still require further research. The book also provides a brief introduction to the main references related to these methods. The content of this book is rich, and in the process of narration, it strives to balance the physical meaning of the conclusions with the rigor of the theory. This book can serve as a textbook for graduate students and senior undergraduate students in control science and engineering, systems science, applied mathematics, and related disciplines. It can also be used as a reference for researchers and teachers in higher education institutions engaged in this field.