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課程名稱 |
智慧型控制
Intelligent Control |
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開課學期 |
103-2 |
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授課對象 |
學程 光機電系統學程 |
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授課教師 |
黃漢邦 |
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課號 |
ME7144 |
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課程識別碼 |
522 M3960 |
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班次 |
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學分 |
3 |
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全/半年 |
半年 |
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必/選修 |
選修 |
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上課時間 |
星期一2,3,4(9:10~12:10) |
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上課地點 |
工綜209 |
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備註 |
光機電學程進階課程
總人數上限：40人 |
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Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/1032ME7144_ |
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課程簡介影片 |
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核心能力關聯 |
核心能力與課程規劃關聯圖 |
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課程大綱
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為確保您我的權利,請尊重智慧財產權及不得非法影印
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課程概述 |
介紹智慧型控制的基本概念、模糊邏輯系統、類神經網路、模糊神經控制、神經模糊控制及機器學習法則等等。使同學對於智慧型控制有一完整的認識，並能進行實際的智慧型控制的設計與應用。 |
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課程目標 |
This course is aimed to introduce intelligent control algorithms and applications. Fuzzy logic control, neural network control, fuzzy-neural system, neural-fuzzy system, and machine learning algorithms will be discussed in the course. It will enable students to understand and apply intelligent control concept and algorithms. |
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課程要求 |
Students are encouraged to take the courses on "Linear Algebra" and "Automatic Control" before taking this course. |
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預期每週課後學習時數 |
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Office Hours |
另約時間 備註： by appointment |
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指定閱讀 |
Course notes |
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參考書目 |
1. C.T. Lin, C.S.G. Lee, Neural Fuzzy Systems. Englewood Cliffs, N.J.: Prentice-Hall, 1996.
2. J.S.R. Jang, C.T. Sun, E. Mizutani, Neuro-Fuzzy and Soft Computing. Englewood Cliffs, N.J.: Prentice-Hall, 1997.
3. H. Li, C.L.P. Chen, H.P. Huang, Fuzzy Neural Intelligent Systems: Mathematical Foundation and the Applications in Engineering, Boca Raton: CRC Press, 2001.
4. G.J. Klir and T. A. Folger, Fuzzy Sets, Uncertainty, and Information. Englewood Cliffs, N.J.: Prentice-Hall, 1988.
5. B. Kosko, Neural Networks and Fuzzy Systems: A Dynamical Systems Approach To Machine Intelligence. Englewood Cliffs, N.J.: Prentice-Hall, 1992.
6. K. Cios, W. Pedrycz, R. Swiniarski, Data Mining Methods for Knowledge Discovery. Boston: Kluwer Academic Publishers, 1998.
7. K.M. Passino, S. Yurkovich, Fuzzy Control. Reading, Massachusetts: Addison-Wesley, 1998.
8. C.V. Negoita, Expert Systems and Fuzzy Systems. London: The Benjamin/Cummings Publ. 1985.
9. W. Pedrycz, Fuzzy Control and Fuzzy Systems. New York: John Wiley & Sons, 1989.
10. P. Wang (ed.), Advances in Fuzzy Sets, Possibility Theory, and Applications. New York: Pleum Press, 1983.
11. R.R. Yager (ed.), Fuzzy Set and Possibility Theory. Oxford: Pergamon Press, 1982.
12. H.J. Zimmermann, Fuzzy Set Theory and Its Applications. 2nd edition, Boston: Kluwer Academic Publishers, 1991.
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評量方式
(僅供參考) |
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No. |
項目 |
百分比 |
說明 |
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1. |
Paper reading, HW and report |
40% |
Paper reading, HW and report |
2. |
Midterm examination |
30% |
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3. |
Final term project |
30% |
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週次 |
日期 |
單元主題 |
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第2週 |
3/02 |
Introduction to intelligent control |
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第3週 |
3/09 |
Introduction to neural networks and fuzzy systems |
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第4週 |
3/16 |
ANN foundation and learning rules |
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第5週 |
3/23 |
Supervised learning |
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第6週 |
3/30 |
Single-layer feedback neural networks |
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第7週 |
4/06 |
Unsupervised learning |
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第8週 |
4/13 |
Unsupervised learning |
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第9週 |
4/20 |
Neural network controller |
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第10週 |
4/27 |
Fuzzy set theory |
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第11週 |
5/04 |
Fuzzy relation |
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第12週 |
5/11 |
Fuzzy inference |
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第13週 |
5/18 |
Midterm Exam |
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第14週 |
5/25 |
Fuzzy control systems |
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第15週 |
6/01 |
Fuzzy neural controller/ Neural fuzzy controller |
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第16週 |
6/08 |
Machining Learning Algorithm (SVM, SVR, GA, etc.) |
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第17週 |
6/15 |
Term Project Presentation |
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第18週 |
06/22 |
Final term project presentation |
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