2018-­02-­27

Systems  Control  and  MechatronicsAI  in  Chalmers  largest  master  program

Division  of  Systems  and  Control,  E2

Prof  Bengt  LennartsonDivision  Head:  Systems  and  ControlDepartment  of  Electrical  EngineeringChalmers  University  of  Technology

2018-­02-­27

Systems  and  Control  (SysCon)IMAGE  SAMPLE

Division  of  Systems  and  Control,  E2 1

• Robotics  &  Automation  Lab• New  Autonomous  Systems  &  Collaborative  Robotics  Lab(5  million  SEK  investment)

70+  members• Automatic  Control• Automation• Mechatronics

Department  of  Electrical  Engineering• Communication  and  Antenna  systems• Signal  processing  and  Biomedical  engineering

• Electric  Power  Engineering• Systems  and  Control

Aerospace

2018-­02-­27 Division  of  Systems  and  Control,  E2 2

Process Industry

Biological Systems

Production Systems Automotive

Power Systems

Embedded Systems

Master  program  in

Systems,  Control  and  MechatronicsAnalysis and synthesis of complex

computer controlled products and systems

2018-­02-­27 Division  of  Systems  and  Control,  E2 3

• Algorithms  and  Artificial   Intelligence

• Autonomous   Systems

• Control  and  Signal  Processing

• Electric  and  Hybrid  Powertrains

• Embedded   Systems

• Industry  4.0

• Machine  Learning

• Mathematical   Systems  Theory

• Power  systems

• Process  control

Course  packages

2018-­02-­27 Division  of  Systems  and  Control,  E2 4

Deep  machine  learning

Content:• Supervised  learning  and  (some)  reinforcement  learning

• Components  and  principles  for  training  neural  networks

• Specialized  networks  for  various  applications

Overview: Deep  neural  networks  for  object  detection,  speech  analysis,machine  translation,  control,  …    

Prof  Lennart  SvenssonSignal  processing

2018-­02-­27 Division  of  Systems  and  Control,  E2 5

Course introduction

A primer in machine learning

Motivating examples

Course information

Flipped classroom teaching

At home In class

Traditional lectureSolve problems Listen to lecture

[alone] [with teacher]

Flipped classroomWatch videos Solve problems

[alone] [with teacher & peers]

Remarks:

– Material is covered by videos )classes dedicated to active learning!

– Students first meet the materialalone and then analyse it with ateacher and peers.

– We have effectively replacedlectures with two teaching elements. Figure: Bloom’s taxonomy of

learning objectives.

Chalmers University of Technology Deep machine learning Lennart Svensson

Flipped  classroom  teaching  &  Adaptive  learning

Adaptive  learning  (Wikipedia)Computerized   educational  

material   is  adapted   to  students'  responses  to  questions,   tasks  

and  experiences.Use  machine   learning   for  

adaptive   learning!

2018-­02-­27 Division  of  Systems  and  Control,  E2 6

• Temporal  logic  planning  and  decision  making,  including  learning  and  adaption.  

• Abstraction  based  state  space  reduction.

• Model  based  reinforcement  learning  (RL)  with  limited  amount  of  data  for  Smart  Assembly.

• Bridging  the  gap  between  formal  optimal  control  and  RL.

• Development  of  RL-­based  tools,  suitable  for  safety  critical  applications.

Expert  advisor Agent Process

Quality  criteria

AI/ML  Research