課程資訊
課程名稱
 智慧型控制
Intelligent Control 
開課學期
 105-2 
授課對象
 工學院  機械工程學研究所  
授課教師
 黃漢邦 
課號
 ME7144 
課程識別碼
 522 M3960 
班次
  
學分
 3.0 
全/半年
 半年 
必/選修
 選修 
上課時間
 星期一2,3,4(9:10~12:10) 
上課地點
 工綜205 
備註
 總人數上限：40人 
Ceiba 課程網頁
 http://ceiba.ntu.edu.tw/1052ME7144_Int 
課程簡介影片
 
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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。 

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. 
課程要求
 Students are encouraged to take the courses on "Linear Algebra" and "Automatic Control" before taking this course. 
預期每週課後學習時數
  
Office Hours
 每週一 13:00~15:00
每週一 13:00~15:00 
指定閱讀
 Class notes 
參考書目
 1. Ian Goodfellow and Yoshua Bengio and Aaron Courville, Deep Learning. Boston: MIT Press, November, 2016.
2. C.T. Lin, C.S.G. Lee, Neural Fuzzy Systems. Englewood Cliffs, N.J.: Prentice-Hall, 1996.
3. J.S.R. Jang, C.T. Sun, E. Mizutani, Neuro-Fuzzy and Soft Computing. Englewood Cliffs, N.J.: Prentice-Hall, 1997.
4. 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.
5. G.J. Klir and T. A. Folger, Fuzzy Sets, Uncertainty, and Information. Englewood Cliffs, N.J.: Prentice-Hall, 1988.
6. B. Kosko, Neural Networks and Fuzzy Systems: A Dynamical Systems Approach To Machine Intelligence. Englewood Cliffs, N.J.: Prentice-Hall, 1992.
7. K. Cios, W. Pedrycz, R. Swiniarski, Data Mining Methods for Knowledge Discovery. Boston: Kluwer Academic Publishers, 1998.
8. K.M. Passino, S. Yurkovich, Fuzzy Control. Reading, Massachusetts: Addison-Wesley, 1998.
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.
13. J.A. Freeman and D.M. Skapura, Neural Networks: Algorithms, Applications, and Programming Techniques. Reading, Massachusetts: Addision-Weslsy Publishing, 1991.
14. S. Grossberg and M. Kuperstein, Neural Dynamics of Adaptive Sensory-Motor Control. Oxford: Pergamon Press, 1989.
15. S. Grossberg (ed.), The Adaptive Brain I & II. Amsterdam:North-Holland, 1987.
16. T. Kohonen, Self-Organization and Associate Memory. 2nd edition, Berlin: Springer-Verlag, 1988.
17. B. Kosko, Neural Networks for Signal Processing. Englewood Cliffs,: Prentice-Hall, 1992.
18. P.K. Simpson, Artificial Neural Systems. Oxford: Pergamon Press, 1990.
19. W.T. Miller III, R.S. Sutton, and P.J. Werbos, (ed.), Neural Networks for Control. Cambridge, Massachusetts: The MIT Press, 1990.
 
評量方式
(僅供參考)
  
No.
項目
百分比
說明
1. 
 Paper reading, HW and report 
40% 
 Paper reading, HW and report 
2. 
 Midterm Exam 
30% 
  
3. 
 Term Project 
30% 
  
 
課程進度
週次
日期
單元主題
第1週
 2/20  Introduction to intelligent control 
第2週
 2/27  彈性放假 
第3週
 3/06  Introduction to neural networks and fuzzy systems 
第4週
 3/13  ANN foundation and learning rules  
第5週
 3/20  Supervised learning  
第6週
 3/27  Single-layer feedback neural networks  
第7週
 4/03  清明節補假 
第8週
 4/10  Unsupervised learning  
第9週
 4/17  Unsupervised learning  
第10週
 4/24  Neural network controller 
第11週
 5/01  Fuzzy set theory 
第12週
 5/08  Fuzzy relation 
第13週
 5/15  Fuzzy inference 
第14週
 5/22  Midterm Exam 
第15週
 5/29  端午節彈性放假 
第16週
 6/03  Fuzzy control systems (補上課) 
第17週
 6/5  Fuzzy neural controller/ Neural fuzzy controller 
第18週
 6/12  Machining Learning Algorithm (Deep learning SVM, GA, etc.) 
第19週
 6/19  Term Project Presentation