Applied Control Engineering

Course Information

College	Tsuyama College	Year	2021
Course Title	Applied Control Engineering
Course Code	0033	Course Category	Specialized / Elective
Class Format	Lecture	Credits	Academic Credit: 2
Department	Advanced Mechanical and Control System Engineering Course	Student Grade	Adv. 2nd
Term	Second Semester	Classes per Week	2
Textbook and/or Teaching Materials
Instructor	TAKETANI Hisashi

Course Objectives

Learning purposes :
Control understands various control methods and keeps the ability by which they can grope after appropriate solution method in technological miscellaneous problems.

Course Objectives :
1. It can be explained about a summary of a neural network, a learning method and movement.
2. It can be explained about a summary of Fuzzy theory.
3. It can be explained about a summary of Genetic Algorithm.

Rubric

	Excellent	Good	Acceptable	Not acceptable
Achievement 1	The student can grasp the feature about various neural networks and apply technologically.	The student can explain specifically about a learning law of a neural network and behavior.	The student can explain the outline about a learning law of a neural network and behavior.	The student dose not reach the following.
Achievement 2	The student can understand the feature of the Fuzzy theory and apply technologically about an easy example.	The student can explain specifically about the contents of Fuzzy theory.	The student can explain the outline about the contents of Fuzzy theory.	The student dose not reach the following.
Achievement 3	The student can apply Genetic Algorithm technologically.	The student can explain specifically about the contents of Genetic Algorithm.	The student can explain the outline about the contents of Genetic Algorithm.	The student dose not reach the following.

Teaching Method

Outline:

General or Specialized : Specialized
Field of learning : Information, measurement and control
Foundational academic disciplines : Engineering/electric electronics and mechanical engineering

Relationship with Educational Objectives :
This class is equivalent to "(2) Knowledge of specialized field technology is acquired and the ability which can be utilized for a design of a machine and a system, a policy and practical use is learned".

Relationship with JABEE programs :
The main goal of learning / education in this class is "(A) and (A-2)", also "(A-1) "is involved.

Course outline :
Control theory as well as development of a computer advance rapidly and diversify. The summary is introduced about the neural network fuzzy theory "and" the genetic algorithm which have become close by electrical appliances recently here.

Style:

Course method :
I print writing on the blackboard in the center and lecture on a summary of general theory and a recent topic using a simulation by a PC.

Grade evaluation method :
Periodic test (70%); A report practice (30%) test can bring writing implements, a calculator and a textbook, etc. in. A make-up isn't put into effect as a principle.

Notice:

Precautions on the enrollment :
This class is "subject which requires learning in schooltime outside". Learning for 45 hours is needed per a semester hour together with learning outside the schooltime concerned and the schooltime. Follow directions of a teacher in charge about learning in schooltime outside.

Course advice :
1. Review the contents of several science and engineering, the computational dynamics and the system control engineering which become a basic subject as the learning of preparations performed beforehand.
2. The former control method is a control method of a new concept which is completely different, but the knowledge of control engineering and information engineering is also needed.

Foundational subjects :
Several science and engineering , computational dynamics and system control engineering etc.

Attendance advice :
The center of these control is software, but large-scale software doesn't make, does easy numerical value calculation and makes it help of understanding here. Therefore always carry calculators. When it's entrance within 20 minutes from class starting, it's made lateness and 1 deficit is done with the department by 3 times of lateness.

Course Plan

			Theme	Goals
2nd Semester
	3rd Quarter
		1st	Guidance and outline	The course contents are understood.
		2nd	Information processing by a creature (1)	Information processing by a creature
		3rd	Information processing by a creature (2)	Information processing by a creature
		4th	Information processing by a creature (3)	Comparison of perishables and a computer
		5th	The outline of an artificial neural network	An artificial neural network model
		6th	Content address memory by a mutual online type neural network	The outline of content address memory
		7th	Solution of combinatorial problem by a mutual online type neural network	The outline of combinatorial problem
		8th	Multi-layer neural network	Behavior of a network and learning algorithm
	4th Quarter
		9th	Deep learning	Mechanism of a multiple network
		10th	Self organizing map(SOM)	The outline of SOM
		11th	Genetic Algorithm(GA) (1)	Basis of GA
		12th	Genetic Algorithm(GA) (2)	Application of GA
		13th	Fuzzy theory (1)	Basic of Fuzzy theory
		14th	Fuzzy theory (2)	Application of Fuzzy theory
		15th	(Periodic exam)
		16th	Answer return and test explanation of a back final exam

Evaluation Method and Weight (%)

	Examination	Presentation	Mutual Evaluations between students	Behavior	Portfolio	Other	Total
Subtotal	70	0	0	0	30	0	100
Basic Proficiency	0	0	0	0	0	0	0
Specialized Proficiency	70	0	0	0	30	0	100
Cross Area Proficiency	0	0	0	0	0	0	0