| 書目名稱 | Stable Adaptive Neural Network Control | | 編輯 | Shuzhi S. Ge,Chang C. Hang,Tao Zhang | | 視頻video | http://file.papertrans.cn/876/875435/875435.mp4 | | 叢書名稱 | The International Series on Asian Studies in Computer and Information Science | | 圖書封面 |  | | 描述 | Recent years have seen a rapid development of neural network control tech- niques and their successful applications. Numerous simulation studies and actual industrial implementations show that artificial neural network is a good candidate for function approximation and control system design in solving the control problems of complex nonlinear systems in the presence of different kinds of uncertainties. Many control approaches/methods, reporting inventions and control applications within the fields of adaptive control, neural control and fuzzy systems, have been published in various books, journals and conference proceedings. In spite of these remarkable advances in neural control field, due to the complexity of nonlinear systems, the present research on adaptive neural control is still focused on the development of fundamental methodologies. From a theoretical viewpoint, there is, in general, lack of a firmly mathematical basis in stability, robustness, and performance analysis of neural network adaptive control systems. This book is motivated by the need for systematic design approaches for stable adaptive control using approximation-based techniques. The main objec- tives of the | | 出版日期 | Book 2002 | | 關(guān)鍵詞 | Adaptive control; Adaptive systems; Nonlinear system; control; control system; control systems; neural net | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4757-6577-9 | | isbn_softcover | 978-1-4419-4932-5 | | isbn_ebook | 978-1-4757-6577-9Series ISSN 1566-0710 | | issn_series | 1566-0710 | | copyright | Springer Science+Business Media New York 2002 |
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