反馈文件质量
lgli/G:\1\springer_new\bok%3A978-981-4585-60-6.pdf
Practical Iterative Learning Control with Frequency Domain Design and Sampled Data Implementation (Advances in Industrial Control) 🔍
Danwei Wang, Yongqiang Ye, Bin Zhang (auth.) Springer-Verlag Singapur, Advances in Industrial Control, Advances in Industrial Control, 1, 2014
英语 [en] · PDF · 8.4MB · 2014 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc/scihub/zlib · Save
描述
This book is on the iterative learning control (ILC) with focus on the design and implementation. We approach the ILC design based on the frequency domain analysis and address the ILC implementation based on the sampled data methods. This is the first book of ILC from frequency domain and sampled data methodologies. The frequency domain design methods offer ILC users insights to the convergence performance which is of practical benefits. This book presents a comprehensive framework with various methodologies to ensure the learnable bandwidth in the ILC system to be set with a balance between learning performance and learning stability. The sampled data implementation ensures effective execution of ILC in practical dynamic systems. The presented sampled data ILC methods also ensure the balance of performance and stability of learning process. Furthermore, the presented theories and methodologies are tested with an ILC controlled robotic system. The experimental results show that the machines can work in much higher accuracy than a feedback control alone can offer. With the proposed ILC algorithms, it is possible that machines can work to their hardware design limits set by sensors and actuators. The target audience for this book includes scientists, engineers and practitioners involved in any systems with repetitive operations.
Erscheinungsdatum: 08.07.2014
备用文件名
lgrsnf/G:\1\springer_new\bok%3A978-981-4585-60-6.pdf
备用文件名
nexusstc/Practical Iterative Learning Control with Frequency Domain Design and Sampled Data Implementation/c0fadd28091c7356c59e72a94c23cfd4.pdf
备用文件名
scihub/10.1007/978-981-4585-60-6.pdf
备用文件名
zlib/Computers/Danwei Wang, Yongqiang Ye, Bin Zhang (auth.)/Practical Iterative Learning Control with Frequency Domain Design and Sampled Data Implementation_2468269.pdf
备选标题
Practical Iterative Learning Control with Frequency Domain Design and Sampled Data Implementation [recurso electrónico
备选作者
Wang, Danwei, Ye, Yongqiang, Zhang, Bin
备用出版商
Springer Science + Business Media Singapore Pte Ltd
备用出版商
Springer Singapore : Imprint : Springer
备用出版商
Springer Singapore Pte. Limited
备用出版商
Springer Nature Singapore
备用版本
Advances in industrial control, Singapore, 2014
备用版本
Advances in Industrial Control, uuuu
备用版本
Springer Nature, Heidleberg, 2014
备用版本
Singapore, Singapore
元数据中的注释
sm29634225
元数据中的注释
{"container_title":"Advances in Industrial Control","edition":"1","isbns":["9789814585590","9789814585606","9814585599","9814585602"],"issns":["1430-9491","2193-1577"],"last_page":226,"publisher":"Springer","series":"Advances in Industrial Control"}
备用描述
"This book is on the iterative learning control (ILC) with focus on the design and implementation. We approach the ILC design based on the frequency domain analysis and address the ILC implementation based on the sampled data methods. This is the first book of ILC from frequency domain and sampled data methodologies. The frequency domain design methods offer ILC users insights to the convergence performance which is of practical benefits. This book presents a comprehensive framework with various methodologies to ensure the learnable bandwidth in the ILC system to be set with a balance between learning performance and learning stability. The sampled data implementation ensures effective execution of ILC in practical dynamic systems. The presented sampled data ILC methods also ensure the balance of performance and stability of learning process. Furthermore, the presented theories and methodologies are tested with an ILC controlled robotic system. The experimental results show that the machines can work in much higher accuracy than a feedback control alone can offer. With the proposed ILC algorithms, it is possible that machines can work to their hardware design limits set by sensors and actuators. The target audience for this book includes scientists, engineers and practitioners involved in any systems with repetitive operations." -- Font no determinada
备用描述
Front Matter....Pages i-xii
Introduction....Pages 1-24
Learnable Band Extension and Multi-channel Configuration....Pages 25-51
Learnable Bandwidth Extension by Auto-Tunings....Pages 53-73
Reverse Time Filtering Based ILC....Pages 75-102
Wavelet Transform Based Frequency Tuning ILC....Pages 103-126
Learning Transient Performance with Cutoff-Frequency Phase-In....Pages 127-152
Pseudo-Downsampled ILC....Pages 153-179
Cyclic Pseudo-Downsampled ILC....Pages 181-209
Possible Future Research....Pages 211-213
Back Matter....Pages 215-226
开源日期
2014-11-10
更多信息……

🚀 快速下载

成为会员以支持书籍、论文等的长期保存。为了感谢您对我们的支持，您将获得高速下载权益。❤️
如果您在本月捐款，您将获得双倍的快速下载次数。

🐢 低速下载

由可信的合作方提供。 更多信息请参见常见问题解答。 （可能需要验证浏览器——无限次下载！）

所有选项下载的文件都相同，应该可以安全使用。即使这样，从互联网下载文件时始终要小心。例如，确保您的设备更新及时。
显示外部下载
  • 对于大文件，我们建议使用下载管理器以防止中断。
    推荐的下载管理器：JDownloader
  • 您将需要一个电子书或 PDF 阅读器来打开文件，具体取决于文件格式。
    推荐的电子书阅读器：Anna的档案在线查看器、ReadEra和Calibre
  • 使用在线工具进行格式转换。
    推荐的转换工具：CloudConvert和PrintFriendly
  • 您可以将 PDF 和 EPUB 文件发送到您的 Kindle 或 Kobo 电子阅读器。
    推荐的工具：亚马逊的“发送到 Kindle”和djazz 的“发送到 Kobo/Kindle”
  • 支持作者和图书馆
    ✍️ 如果您喜欢这个并且能够负担得起，请考虑购买原版，或直接支持作者。
    📚 如果您当地的图书馆有这本书，请考虑在那里免费借阅。