Synopsis
This comprehensive text provides an excellent introduction to the state of the art in the identification of network-connected systems. It covers models and methods in detail, includes a case study showing how many of these methods are applied in adaptive optics and addresses open research questions. Specific models covered include generic modelling for MIMO LTI systems, signal flow models of dynamic networks and models of networks of local LTI systems. A variety of different identification methods are discussed, including identification of signal flow dynamics networks, subspace-like identification of multi-dimensional systems and subspace identification of local systems in an NDS. Researchers working in system identification and/or networked systems will appreciate the comprehensive overview provided, and the emphasis on algorithm design will interest those wishing to test the theory on real-life applications. This is the ideal text for researchers and graduate students interested in system identification for networked systems.
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About the Authors
Michel Verhaegen is a professor at Delft University of Technology and a fellow of the International Federation of Automatic Control (IFAC). He co-authored Filtering and System Identification: A Least Squares Approach (Cambridge University Press, 2010).
Chengpu Yu is a professor at Beijing Institute of Technology.
Baptiste Sinquin is an algorithm engineer at SYSNAV.
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Data-Driven Identification of Networks of Dynamic Systems (Hardcover)
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Hardcover. Condition: new. Hardcover. This comprehensive text provides an excellent introduction to the state of the art in the identification of network-connected systems. It covers models and methods in detail, includes a case study showing how many of these methods are applied in adaptive optics and addresses open research questions. Specific models covered include generic modelling for MIMO LTI systems, signal flow models of dynamic networks and models of networks of local LTI systems. A variety of different identification methods are discussed, including identification of signal flow dynamics networks, subspace-like identification of multi-dimensional systems and subspace identification of local systems in an NDS. Researchers working in system identification and/or networked systems will appreciate the comprehensive overview provided, and the emphasis on algorithm design will interest those wishing to test the theory on real-life applications. This is the ideal text for researchers and graduate students interested in system identification for networked systems. An excellent introduction to the identification of network-connected systems, covering models and methods in detail, demonstrating how these methods are applied in adaptive optics, and addressing open questions. Researchers and graduate students in system identification and networked systems will appreciate this comprehensive overview. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781316515709
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Hardcover. Condition: new. Hardcover. This comprehensive text provides an excellent introduction to the state of the art in the identification of network-connected systems. It covers models and methods in detail, includes a case study showing how many of these methods are applied in adaptive optics and addresses open research questions. Specific models covered include generic modelling for MIMO LTI systems, signal flow models of dynamic networks and models of networks of local LTI systems. A variety of different identification methods are discussed, including identification of signal flow dynamics networks, subspace-like identification of multi-dimensional systems and subspace identification of local systems in an NDS. Researchers working in system identification and/or networked systems will appreciate the comprehensive overview provided, and the emphasis on algorithm design will interest those wishing to test the theory on real-life applications. This is the ideal text for researchers and graduate students interested in system identification for networked systems. An excellent introduction to the identification of network-connected systems, covering models and methods in detail, demonstrating how these methods are applied in adaptive optics, and addressing open questions. Researchers and graduate students in system identification and networked systems will appreciate this comprehensive overview. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781316515709
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