Experiments on System Engineering Ⅲ

Course Information

College	Toyama College	Year	2022
Course Title	Experiments on System Engineering Ⅲ
Course Code	0122	Course Category	Specialized / Compulsory
Class Format	Experiment / Practical training	Credits	School Credit: 1
Department	Department of Electrical and Control Systems Engineering	Student Grade	5th
Term	First Semester	Classes per Week	2
Textbook and/or Teaching Materials	e-Learning system, Handouts
Instructor	Kaneko Shinichiro,Kitamura Takuya

Course Objectives

At the completion of this course, students will be able to

1) Understand how to operate the MATLAB system.
2) Understand Python language usage and programming method.
3) Understand basic statistical algorithms.
4) Acquire logical reporting skills by summarizing the results gained through practical training.

Rubric

	Ideal Level of Achievement (Very Good)	Standard Level of Achievement (Good)	Unacceptable Level of Achievement (Fail)
Evaluation 1	Can understand the operation method of MATLAB system correctly and perform basic simulation.	Can nderstand how to operate the MATLAB system.	Can not understand how to operate the MATLAB system.
Evaluation 2	Can understand how to use the Python language and develop an advanced program.	Can understand how to use Python language and can create basic programs.	Can not use the Python language and can not create basic programs.
Evaluation 4	Can understand basic statistical algorithms and explain correctly.	Can understand basic statistical algorithms.	Can not understand basic statistical algorithms.
Evaluation 5	Can create objective reports based on the specified format.	Can comply with the specified format and create a report.	Can not comply with the specified format and create reports.

Assigned Department Objectives

学習・教育到達度目標 A-3 （実験を計画・実施し，データの正確な解析に基づいて工学的に考察し，かつ論理的に説明することができる。研究においては与えられた制約の下で必要な援助を得て計画的に研究を進め，期限内にまとめることができる。）

JABEE 1(2)(c) （数学及び自然科学に関する知識とそれらを応用する能力）

JABEE 1(2)(d)(2) （いくつかの工学の基礎的な知識・技術を駆使して実験を計画・遂行し、データを正確に解析し、工学的に考察し、かつ説明・説得する能力）

JABEE 1(2)(h) （与えられた制約の下で計画的に仕事を進め、まとめる能力）

ディプロマポリシー 2 （課題発見能力，課題解決能力，プレゼンテーション能力を持ち，他者と協働できる。）

Teaching Method

Outline:

Students will learn about programming and simulation using MATLAB and R languages based on subjects of mathematics, machinery, electricity and control systems learned by grade 4.
In R language, students practically will program various statistical algorithms. In MATLAB, students will learn the basic operation of the system, compare the simulation with the experiment data of the inverted pendulum robot and understand the meaning of control.

Style:

Lecture and practice
Class is divided into two groups, first half and second half, and each theme is learned.

Notice:

Students should listen to the prior explanation before the experiment.
Also, carefully read the handouts and grasp the contents of the experiment.

Can take makeup exam in need aid up to maximum of 60 points.

Characteristics of Class / Division in Learning

Aided by ICT

Course Plan

			Theme	Goals
1st Semester
	1st Quarter
		1st	Guidance ・Explanation about contents of practical training	Understand the outline, schedule, and notes of the practical training.
		2nd	First half group: MATLAB practical training Second half group: Python language practice	First half group ・Understand e-Learning system, how to use MATLAB. Second half group ・Understand how to use Python language.
		3rd	First half group: MATLAB practical training Second half group: Python language practice	First half group · Understand MATLAB programming using MATLAB IDE. Second half group · Understand Python programming using lecture materials.
		4th	First half group: MATLAB practical training Second half group: Python language practice	First half group · Understand MATLAB programming using MATLAB IDE. Second half group · Understand Python programming using lecture materials.
		5th	First half group: MATLAB practical training Second half group: Python language practice	First half group · Understand SimuLink programming using MATLAB IDE. Second half group · Understand Python programming using lecture materials.
		6th	First half group: MATLAB practical training Second half group: Python language practice	First half group · Understand SimuLink programing using MATLAB IDE. Second half group · Understand Python programing using lecture materials.
		7th	First half group: MATLAB practical training Second half group: Python language practice	First half group · Understand SimuLink simulation using MATLAB IDE. Second half group · Understand Python programming using lecture materials.
		8th	First half group: Python language practice Second half group: MATLAB practical training	First half group ・Understand how to use Python language. Second half group ・Understand e-Learning system, how to use MATLAB.
	2nd Quarter
		9th	First half group: Python language practice Second half group: MATLAB practical training	First half group · Understand Python programming using lecture materials. Second half group · Understand MATLAB programming using MATLAB IDE.
		10th	First half group: Python language practice Second half group: MATLAB practical training	First half group · Understand Python programming using lecture materials. Second half group · Understand MATLAB programming using MATLAB IDE.
		11th	First half group: Python language practice Second half group: MATLAB practical training	First half group · Understand Python programming using lecture materials. Second half group · Understand SimuLink programming using MATLAB IDE.
		12th	First half group: Python language practice Second half group: MATLAB practical training	First half group · Understand Python programming using lecture materials. Second half group · Understand SimuLink programming using MATLAB IDE.
		13th	First half group: Python language practice Second half group: MATLAB practical training	First half group · Understand Python programming using lecture materials. Second half group · Understand SimuLink simulation using MATLAB IDE.
		14th	Preparation day Report creation	Create a report.
		15th	Preparation day Report creation	Complete the report.
		16th	Summary Questionnaire

Evaluation Method and Weight (%)

	Examination	Presentation	Mutual Evaluations between students	Behavior	Portfolio	Other	Total
Subtotal	100	0	0	0	0	0	100
Basic Ability	50	0	0	0	0	0	50
Technical Ability	50	0	0	0	0	0	50
Interdisciplinary Ability	0	0	0	0	0	0	0