| 書(shū)目名稱 | Iterative Learning Control for Deterministic Systems |
| 編輯 | Kevin L. Moore |
| 視頻video | http://file.papertrans.cn/477/476572/476572.mp4 |
| 叢書(shū)名稱 | Advances in Industrial Control |
| 圖書(shū)封面 |  |
| 描述 | The material presented in this book addresses the analysis and design of learning control systems. It begins with an introduction to the concept of learning control, including a comprehensive literature review. The text follows with a complete and unifying analysis of the learning control problem for linear LTI systems using a system-theoretic approach which offers insight into the nature of the solution of the learning control problem. Additionally, several design methods are given for LTI learning control, incorporating a technique based on parameter estimation and a one-step learning control algorithm for finite-horizon problems. Further chapters focus upon learning control for deterministic nonlinear systems, and a time-varying learning controller is presented which can be applied to a class of nonlinear systems, including the models of typical robotic manipulators. The book concludes with the application of artificial neural networks to the learning control problem. Three specificways to neural nets for this purpose are discussed, including two methods which use backpropagation training and reinforcement learning. The appendices in the book are particularly useful because they |
| 出版日期 | Book 1993 |
| 關(guān)鍵詞 | Extension; algorithms; artificial neural network; artificial neural networks; associative memory; backpro |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4471-1912-8 |
| isbn_softcover | 978-1-4471-1914-2 |
| isbn_ebook | 978-1-4471-1912-8Series ISSN 1430-9491 Series E-ISSN 2193-1577 |
| issn_series | 1430-9491 |
| copyright | Springer-Verlag London Limited 1993 |
|Archiver|手機(jī)版|小黑屋|
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