Enrolment options

Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

After completing the course, a student can select proper modeling approach for specific practical problems, formulate mathematical models of physical systems, construct models of systems using modeling tools such as MATLAB and Simulink, and estimate the parameters of linear and nonlinear static systems and linear dynamic systems from measurement data.

Credits: 5

Schedule: 15.09.2021 - 14.12.2021

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Quan Zhou, Kai Zenger

Contact information for the course (applies in this implementation):

Responsible teacher: Prof. Quan Zhou, quan.zhou@aalto.fi

Other teachers/assistants:

  • M.Sc. Artur Kopitca, artur.kopitca@aalto.fi
  • M.Sc. Ogulcan Isitman, ogulcan.isitman@aalto.fi
  • Dr. Hakan Kandemir, hakan.kandemir@aalto.fi
  • Dr. Houari Bettahar, houari.bettahar@aalto.fi

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content
  • valid for whole curriculum period:

    Basic modeling methods, including first principle modeling and data-driven modeling, for both static and dynamic systems: first principle modeling, black box modeling, basics of regression methods, static parameter estimation for linear and non-linear systems, identification of linear time-invariant dynamical systems, model validation.

Assessment Methods and Criteria
  • valid for whole curriculum period:

    The final grade will take into acount both the home assignments and the final exam. The actual distribution to be specified.

  • applies in this implementation

    The course will be evaluated by five home exercises and the final exercise.

    • Home exercise 1-5 (8 percentage points for each exercise, 40 percentage points in total). Exercise sessions will be held to help you conduct each of the exercises. The points for home exercises will be given if you demonstrate sufficient efforts. Standard answers will be published after each submission deadline.
    • Final home exercise (60 percentage points). The points will be given based on the correctness of your submission. The final home exercise replaces the exam, so no discussion is allowed, and there will be also no exercise session for the final exercise.
    • The final grade will be given based on your total points: [50%, 60%) → 1,  [60, 70%) → 2, [70%, 80%) → 3, [80%, 90%) → 4, [90%, inf] → 5. 

    The evaluation criteria will be clarified/revised in the first lecture.

Workload
  • valid for whole curriculum period:

    Lectures, exercise sessions, independent study and problem solving, home assignments.

    Contact hours: 24 + 12 h
    Independent study: 93 h

     

  • applies in this implementation

    • There will be 11 lectures. The purpose of the lecture is not to teach everything about modeling, but to provide you a general theoretical background and some guidance on selected practical tools. The lectures are held only in certain weeks: W37, W39, W41, W44, W46, and possibly W48. For each lecture week, there are two lectures: Wednesday 12:15-14:00 and Thursday 12:15-14:00. 
    • There will be 5 exercise sessions. You should already work on your exercises before you come to the exercises sessions. The purpose of the exercise is to help you to solve the problems you encounter doing the exercises, not to teach you how to solve the exercieses, even though generalized problems students encounter will be highlighted. The exercise sessions will be held in certain weeks: W38, W40, W42, W45, W47.
    • The exercise sessions will be held online per exercise week. There will be 3-4 instances of the same exercise sessions, where you should only attend one. The exercise session time slots are: Monday 14:15-16:00, 16:15-18:00, Wednesday 12:15-14:00, 16:15-18:00.
    • The exercise sessions are not mandatory but highly recommended. You should already work on your exercises before you come to the exercises sessions.
    • The final home exercise will be online, held during 2.12-8.12.2021 (tentative), the submission will be via MyCourses.
    How the learning is done in the course:
    Theoretical lectures
    • Theoretical background (what is behind the tools, how things work)
    Practical lectures
    • How to use tools
    Home exercises
    • Deep learning of the course contents
    Exercise sessions
    • Personalized learning / mentoring

DETAILS

Study Material
  • valid for whole curriculum period:

    Handouts/lecture slides, Ljung, Modeling of dynamic systems, 1994, additional book chapters.

  • applies in this implementation

    The main course materials are the lecture handouts (in the Materials section). The additional readings of each lecture will be given at the end of each lecture.


Substitutes for Courses
Prerequisites

FURTHER INFORMATION

Further Information
  • valid for whole curriculum period:

    Teaching Period:

    2020-2021 Autumn I-II

    2021-2022 Autumn I-II

    Course Homepage: https://mycourses.aalto.fi/course/search.php?search=ELEC-E8103

    Registration for Courses: In the academic year 2021-2022, registration for courses will take place on Sisu (sisu.aalto.fi) instead of WebOodi.

    WebOodi

  • applies in this implementation

    • All teaching activities (lectures, exercise sessions) of this course will be held online using Zoom. The possibility of having on-site exercise sessions will be decided depending on demand and feasibility (to be updated later). 
    • The first lecture will be held on Wednesday, September 15, 2021, at 12:15. 
    • The final home exercise (= exam) will be held online with a duration of about one week.

Details on the schedule
  • applies in this implementation

     M 

     T 

     W 

     T 

     F 

     S 

     S 

    W35-36

    Starting survey

    W37

    12:15-14:00 Introduction

    12:15-14:00 Physical modelling

    EX1 assigned

    W38

    14:15-16:00 EX1_1, 16:15-18:00 EX1_2

    12:15-14:00 EX1_3, 16:15-18:00 (EX1_4)

    DL EX1

    W39

    12:15-14:00 Simulation

    12:15-14:00 Simulink

    EX2 assigned

    W40

    14:15-16:00 EX2_1, 16:15-18:00 EX2_2

    12:15-14:00 EX2_3, 16:15-18:00 (EX2_4)

    DL EX2

    W41

    12:15-14:00 Regression

    12:15-14:00 Curve fitting

    EX3 assigned

    W42

    14:15-16:00 EX3_1, 16:15-18:00 EX3_2

    12:15-14:00 EX3_3, 16:15-18:00 (EX3_4)

    DL EX3

    W43

    Break 

    Mid-term survey

    W44

    12:15-14:00 Analysis of dynamic systems

    12:15-14:00 Parameter estimation

    EX4 assigned

    W45

    14:15-16:00 EX4_1, 16:15-18:00 EX4_2

    12:15-14:00 EX4_3, 16:15-18:00 (EX4_4)

    DL EX4

    W46

    12:15-14:00 System identification 1

    12:15-14:00 System identification 2

    EX5 assigned

    W47

    14:15-16:00 EX5_1, 16:15-18:00 EX5_2

    12:15-14:00 EX5_3, 16:15-18:00 (EX5_4)

    DL EX5

    W48

    Final Lecture (tentative)

    Final EX6 assigned (tentative)

    W49

    DL EX6 (tentative)

    Note:

    • Each exercise (EX1 - EX5) will have guided exercise sessions.
    • Depending on the number of students, the guided exercise session will be held 3-4 times (EXn_1 - EXn_4). You should only attend one of them. 
    • In 2021, EXn_1 and EXn_2 will be held on-site, EXn_3 and EXn_4 will be held online.
    • The attendance of the exercise sessions is not mandatory, more details of the arrangement of the guided exercise sessions will be instructed later.

Guests cannot access this workspace. Please log in.