Course Syllabus

Course Information：

Year-Semester Course Number Course Name Phase Credits Hours Required/Elective Instructor Class Student NO. Withdraw Note

Spring Semester
Year 2024 328524 Intelligent Control 1 3.0 3 ★ Shiao,Yaojung GVE
IMPEV
DME 8 1 車輛所、車輛能源外生和機電博班合開

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2024	328524	Intelligent Control	1	3.0	3	★	Shiao,Yaojung	GVE IMPEV DME	8	1	車輛所、車輛能源外生和機電博班合開

Course Plan：

Instructor Shiao,Yaojung　Office Hours

Email yshiao@ntut.edu.tw

Last Updated 2024-04-25 00:33:06

Course Objective This course will teach the knowledge-based control methods, mainly focuses on Fuzzy logic control and Gray system (and neural network if time is available). The Fuzzy method includes Fuzzy Logic theory and Fuzzy Logic Control. From this course, students can understand Fuzzy theory and can apply FLC and Grey in mechanical, electrical, or vehicle systems. The topics covered in this lecture include: fuzzy set, membership function, fuzzification / defuzzification, fuzzy reasoning and inference, FLC design, FLC applications, grey theory, grey prediction, gray modeling, and grey control (and neural-network if time is available). This lecture needs all students to do a 2- or 3-person team project to design and implement a fuzzy logic control to a real system. Before the core lessons, a review of system dynamics will be provided.

Course Schedule week course content 1 Introduction and Fuzzy logic 2 review of control system dynamics 3 Fuzzy sets / Fuzzy relations term project announce 4 Fuzzy graphs and arithmetic Fuzzy rules 5 workshop I - membership function 6 Fuzzy implications 7 Fuzzy approximate reasoning / Fuzzy logic and probability 8 workshop II - LabVIEW programming I 9 workshop III - LabVIEW programming II / Signals and DAQ 10 Fuzzy logic control 11 Design of Fuzzy controller 12 Design of Fuzzy controller 13 workshop IV – tuning controller 14 writing Exam 15 Fuzzy PID control / TSK fuzzy control 16 grey theory 17 project presentation and demonstration 18 project discussion * might be adjusted according to student learning situation

Evaluation and grading policy midterm exam: 40% project reports, demonstration and presentation: 45% workshop 10% class performance: 5% * might be adjusted according to student learning situation

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:Yes
textbook: A Course in Fuzzy Systems and Control, by Li-Xin Wang, published by Prentice Hall reference book: 1. Fuzzy Logic with Engineering Applications, by Timothy Ross 2. class notes

The access to curricular consultation yshiao@ntut.edu.tw

The course corresponds to the SDGs

Note
project presentation and demonstration will move to Week 16.
Week 17: on-line instruction meet.google.com/hqy-kqxp-vwj
Week 18: on-line instruction meet.google.com/hqy-kqxp-vwj

Instructor	Shiao,Yaojung　Office Hours
Email	yshiao@ntut.edu.tw
Last Updated	2024-04-25 00:33:06
Course Objective	This course will teach the knowledge-based control methods, mainly focuses on Fuzzy logic control and Gray system (and neural network if time is available). The Fuzzy method includes Fuzzy Logic theory and Fuzzy Logic Control. From this course, students can understand Fuzzy theory and can apply FLC and Grey in mechanical, electrical, or vehicle systems. The topics covered in this lecture include: fuzzy set, membership function, fuzzification / defuzzification, fuzzy reasoning and inference, FLC design, FLC applications, grey theory, grey prediction, gray modeling, and grey control (and neural-network if time is available). This lecture needs all students to do a 2- or 3-person team project to design and implement a fuzzy logic control to a real system. Before the core lessons, a review of system dynamics will be provided.
Course Schedule	week course content 1 Introduction and Fuzzy logic 2 review of control system dynamics 3 Fuzzy sets / Fuzzy relations term project announce 4 Fuzzy graphs and arithmetic Fuzzy rules 5 workshop I - membership function 6 Fuzzy implications 7 Fuzzy approximate reasoning / Fuzzy logic and probability 8 workshop II - LabVIEW programming I 9 workshop III - LabVIEW programming II / Signals and DAQ 10 Fuzzy logic control 11 Design of Fuzzy controller 12 Design of Fuzzy controller 13 workshop IV – tuning controller 14 writing Exam 15 Fuzzy PID control / TSK fuzzy control 16 grey theory 17 project presentation and demonstration 18 project discussion * might be adjusted according to student learning situation
Evaluation and grading policy	midterm exam: 40% project reports, demonstration and presentation: 45% workshop 10% class performance: 5% * might be adjusted according to student learning situation
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes textbook: A Course in Fuzzy Systems and Control, by Li-Xin Wang, published by Prentice Hall reference book: 1. Fuzzy Logic with Engineering Applications, by Timothy Ross 2. class notes
The access to curricular consultation	yshiao@ntut.edu.tw
The course corresponds to the SDGs
Note	project presentation and demonstration will move to Week 16. Week 17: on-line instruction meet.google.com/hqy-kqxp-vwj Week 18: on-line instruction meet.google.com/hqy-kqxp-vwj