1 Introduction to Problem based Learning – The AAU Way Program: Monday : Structure, teaching task's, courses, Tuesday : The Aalborg model - trying it out, PBL/Project Work and Assessment Wednesday : Supervision Coffee break's at ap and Lunch at 12.00

2 Introduction to Problem based Learning – The AAU Way Program for to day, Structure, teaching task's, courses : Welcome Introduction and short presentation Structure and conditions Teaching task's Courses Exercises

3 Structure of Aalborg University Welcome to Aalborg University

4 Structure of Aalborg University University Senate Rectorate Faculty of Humanities Faculty of Engi- neering and Sc. Faculty of Social Science Departments Study Programmes

5 Secretary and labs Research Teaching Structure of Aalborg University University Senate Rectorate Faculty of Humanities Faculty of Engi- neering and Sc. Faculty of Social Science Institute of Elec- tronic Systems Study Programmes

6 Project work Course activities Secretary and labs Research Teaching Structure of Aalborg University University Senate Rectorate Faculty of Humanities Faculty of Engi- neering and Sc. Faculty of Social Science Institute of Elec- tronic Systems Computer Eng. Electronic and.

7 Working tasks for VIP’s ProfessorAssociated Professor Assistent Professor Ph.D. student Research40% 45%83% Teaching60% 55%17% Teaching In hours 497 h 456 h140 h

8 Study board for Electronics and Information Technology

9 Controlling the studies Study Regulations: General regulations

10 Controlling the studies Study Regulations: General regulations Sector’s, lines or specialization’s –Objectives and content 4.6. INTELLIGENT AUTONOMOUS SYSTEMS Objectives and contents of the specialisation The objectives of the specialisation in Intelligent Autonomous Systems are summarised as follows: to provide students with knowledge in modelling of mechanical systems such as spacecraft, ships, and mobile robots, enable the student to apply modern methods of control to problems related to autonomous systems, to analyse methods of state observation, parameter estimation and sensor fusion in mechanical systems, to provide students with a comprehension of supervisory control, fault-tolerant control and fault detection, to let students analyse software architectures for autonomous systems. The courses include necessary general theoretical topics within process control for autonomous systems but modules are also made available in scientific communication and proficiency in English language for those who need it.

11 Controlling the studies Study Regulations: General regulations Sector’s, lines or specialization’s –Objectives and content Specific semesters –Theme SPRING Semester – Intelligent Autonomous Systems THEME: Modelling and Control PERIOD: 1 February - 30 June PURPOSE: To give knowledge and comprehension of optimal and robust control theory. To give the students the ability to analyse modern control methods for multi input/multi output systems. To give students the ability to apply modelling methods and control synthesis for advanced mechanical systems. CONTENTS: The project is based on a problem of control and supervision of an autonomous system. The model of the mechanical system has to be derived. The vital part of the project is the choice of the set of actuators and sensors for onboard application. Different control strategies have to be investigated and compared. The supervisor system responsible for autonomy onboard has to be designed. The chosen solution has to be implemented on a real time platform and tested, either by the computer simulations or dedicated hardware. COURSES: Courses will be given in the field of modelling of mechanical systems, supervisory and fault tolerant control, and modern control theory. EXAM: The external oral examination is based on the prepared project documentation. Each student is marked according to the 13-scale.

12 Controlling the studies Study Regulations: General regulations Sector’s, lines or specialization’s –Objectives and content Specific semesters –Theme –Projects Model based tracking for navigation Background As part of an ongoing research project (with Computer Science AAU and The Danish Institute of Agricultural Sciences) an autonomous vehicle is developed which navigates autonomously in the field. The aim is to reduce the inputs to the field and monitor the growth of the individual plants, thereby providing obvious environmental and economic advantages over more traditional farming. Purpose It is important in such applications to both navigate accurately in the field but also to be able to identify individual plants. The aim in this project is to use perspective images captures from a camera mounted on the front of the vehicle to provide estimates of structure of the crop rows as well as position of the individual plants. The focus will not be on the image analysis but on sensor fusion with non-vision sensors mounted on the vehicle e.g. wheel encoders, differential GPS as well as integration of information about the known structure of the field. The aim is to use all available information on the autonomous vehicle in order to achieve the best possible estimates of the vehicle and individual plant position (in the order of cm). Methods The project will include: Modeling of vehicle system and plant pattern in the camera image Prediction of the crop structure based on the system models as well as previous measurements (images and data from sensors) Estimation of vehicle position and orientation as well as plant position Algorithms are simulated in the laboratory on simple setup. If possible the algorithms are applied to data acquired in the field.

13 Controlling the studies Study Regulations: General regulations Sector’s, lines or specialization’s –Objectives and content Specific semesters –Theme –Projects –Courses Study related courses (SE): Fault Detection and Automated Systems Modelling of Mechanical Systems Controller Structures Modelling of Mechanical Systems II Engineering Responsibilities Project related courses (PE): Robust Control Optimal Control Supervisory Control Neural Networks and Fuzzy Logic Project Management and Team Building

14 Controlling the studies Study Regulations: General regulations Sector’s, lines or specialization’s –Objectives and content Specific semesters –Theme –Projects –Courses –Semester group

15 Teaching task’s Project Project courses lectures seminar Study courses and lectures Examination 50% - 33% 50% - 67% Lecturer/instructor Supervisor: Advisor and facilitator Examinor/censor Examinor Structure of a semester:

16 Courses Description Course Description Optimal Control Theory Purpose: To give the students knowledge in optimal control and practical experience with optimal control strategies based on minimisation of a performance index. Contents: Dynamic programming LQ control Introduction of reference and disturbance conditions Introduction of integral conditions Use of observer, LQG control The position of closed loop poles Prerequisites: Analogue and Digital Control (FP6-4, PR6-1, PR6-2), Stochastic systems (FP6-3, FP8-5) Duration: 1 module Category: Project theme course (PE- course)

17 Courses Description Placed in a timetable for the semester

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20 Courses Description Placed in a timetable for the semester Syllabus

21 Courses Each lesson/lecture (Mini module): Duration 3 hours 45 minutes (½ day) 2 lectures app. 45 min each Exercises in groups, app. 2 hours –The lecturer is now instructor The purpose of the combination of lectures/exercises is to increase the comprehension of the curriculum

22 Courses What kind of exercises would you chose? Promote comprehension and methodical ness How will you act as instructor during the exercises in the groups? Ask questions about how they have made their solution Make sure that they have understood the basic principles of the problems

23 Courses Differences between project course (PE) and study course (SE) Examination –PE has no formal examination by the lecturer, it is examined during the project examination by the supervisor –SE is examined by the lecturer, normally as a written examination (passed/non passed) Exercises –PE is used in the project, exercises is examples –In SE the student must learn to solve examination exercises

24 Lunch until 12.45

25 Course exercise Think of an engineering subject you all know something about Suppose that you have to do a course on that subject Make a short exercise that will learn the students the major point of a specific part of your course

26 Course exercise continued For one group at a time do: Give your exercise to the other three groups who starts solving it Prepare how you will instruct the groups during their problem solving After 5-10 minutes of problem solving 2 persons from your group enters each of the other groups and starts acting as an instructor