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101 0 $aeng
135   $aur|||||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 00$aComplex Dynamic System Modelling, Identification and Control /$fQuanmin Zhu and [four others], editors
210  1$aBasel :$cMDPI - Multidisciplinary Digital Publishing Institute,$d2023.
215   $a1 online resource (352 pages)
311   $a3-0365-7660-6 
320   $aIncludes bibliographical references.
330   $aThe study of complex dynamic systems has become increasingly important in recent years due to its wide range of applications in fields such as engineering, physics, economics, and biology. These systems are characterized by their interconnectedness, nonlinearities, and feedback loops, which make them difficult to understand and control. As a result, there has been growing interest in developing tools and techniques for the modelling, identification, and control of complex dynamic systems. The aim of this reprint is to provide an overview of the state-of-the-art methods for the modelling, identification, and control of complex dynamic systems. This reprint covers a wide range of topics, including system identification, model-based control, adaptive control, nonlinear control, and predictive control. It also includes case studies and examples from different fields to demonstrate the practical application of these methods. This reprint is intended for researchers, graduate students, and practitioners in the field of control systems. It assumes a basic understanding of linear systems theory, calculus, and linear algebra. Overall, this reprint provides a comprehensive and up-to-date overview of the methods for the modelling, identification, and control of complex dynamic systems.
606   $aSystem identification
615  0$aSystem identification.
676   $a003
702   $aZhu$b Quanmin
801  0$bNjHacI
801  1$bNjHacl
906   $aBOOK
912   $a9910729786103321
996   $aComplex Dynamic System Modelling, Identification and Control$93392021
997   $aUNINA