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A Modeling Methodology 1. Introduction 2. Representation of Models 3. Units 4. Schematic Diagrams 5. A Water Tank 6. Electrical Circuits 7. Summary A Modeling Methodology ◮ Purpose of modeling: understanding, control design, diagnostics, ... ◮ Cut a system into subsystems ◮ Write mass, momentum and energy balances for each subsystem ◮ Discretize partial differential equations ◮ Add constitutive eq
Differential Algebraic Equations Contents: 1. Introduction 2. Differential Algebraic Equations 3. Linear DAE 4. The Notion of Index 5. Numerical Methods 6. Summary Goal: ◮ To develop a basic understanding of differential-algebraic equations Introduction ◮ Cut a system into subsystems ◮ Use object orientation to structure the system ◮ Write mass, momentum and energy balances for each subsystem ◮ As
https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/PhysicalModeling/Lectures/L4-DAEeight.pdf - 2026-04-24
Mechanical Systems 1. Introduction 2. Astronomy 3. Newton, Lagrange, Hamilton and Jacobi 4. Pendulum on a Cart 5. Furuta Pendulum 6. Ball and Beam 7. Summary Natural Science and Engineering Science Many similarities but also many differences Natural Phenomena Insight Understanding Analysis Isolation Fundamental Laws Technical Systems Insight Understanding Synthesis Interaction System Principles Fe
Friction Models and Friction Compensation Karl J. Åström Department of Automatic Control Lund University 1. Introduction 2. Friction Models 3. The LuGre Model 4. Effects of Friction on Control Systems 5. Friction Compensation 6. Summary Introduction ◮ Essential in Motion Control ◮ Classics Leonardo da Vinci (1452-1519 Amontons 1699 Coulomb 1785 ◮ Tribology ◮ Control ◮ Physics AFM ◮ Surface force a
Bicycle Dynamics and Control Karl Johan Åström Department of Automatic Control LTH, Lund University Thanks to Richard Klein and Anders Lennartsson Why Model? ◮ Insight and understanding ◮ Analysis, Simulation, Virtual reality ◮ Design optimization ◮ Control design ◮ Implementation The internal model principle A process model is part of the controlller ◮ Operator training ◮ Hardware in the loop sim
https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/PhysicalModeling/Lectures/L9A-Bikeseight.pdf - 2026-04-24
MTK for control Physical modeling in Julia For those about to control Acknowledgement This presentation contains an assortment of content contributed by multiple people ● Chris Rackauckas ● Yingbo Ma ● Probably more, thank you! Outline ● X Differential equations ● Equation-based modeling ○ Symbolics ○ ModelingToolkit (MTK) ○ Tools on top of MTK ● MTK Standard library ● Current status ● Project ide
https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/PhysicalModeling/Lectures/MTK_for_control.pdf - 2026-04-24
Optimal Control of RLCT Networks Circuit Theory Richard Pates Who cares? ...classical theory of passive network synthesis–a beautiful subject that reached its zenith around 1960, only to decline steadily thereafter as an active research interest... –Malcolm Smith Who cares? ...classical theory of passive network synthesis–a beautiful subject that reached its zenith around 1960, only to decline ste
PowerPoint Presentation Model-Based Policy Learning CS 285: Deep Reinforcement Learning, Decision Making, and Control Sergey Levine Class Notes 1. Homework 3 is out! Due next week • Start early, this one will take a bit longer! 1. Last time: model-based reinforcement learning without policies 2. Today: model-based reinforcement learning of policies • Learning global policies • Learning local polic
PowerPoint Presentation Reframing Control as an Inference Problem CS 285: Deep Reinforcement Learning, Decision Making, and Control Sergey Levine Class Notes 1. Homework 3 is out! Due Oct 21 • Start early, this one will take a bit longer! Today’s Lecture 1. Does reinforcement learning and optimal control provide a reasonable model of human behavior? 2. Is there a better explanation? 3. Can we deri
PowerPoint Presentation Inverse Reinforcement Learning CS 285: Deep Reinforcement Learning, Decision Making, and Control Sergey Levine Today’s Lecture 1. So far: manually design reward function to define a task 2. What if we want to learn the reward function from observing an expert, and then use reinforcement learning? 3. Apply approximate optimality model from last week, but now learn the reward
Study Circle in Deep Reinforcement Learning Lecture 0 Gautham Nayak Seetanadi Dept. of Automatic Control, Lund Institute of Technology February 9, 2021 Study Circle I We will follow online courses and assignments I The topics might change over time I Happy for input or suggestions for the course I Current course ends Mid-April. Might speed up at the end I Active participation in course for credits
Deep RL Assignment 1: Imitation Learning Fall 2019 due September 16th, 11:59 pm The goal of this assignment is to experiment with imitation learning, including direct behavior cloning and the DAgger algorithm. In lieu of a human demonstrator, demonstrations will be provided via an expert policy that we have trained for you. Your goals will be to set up behavior cloning and DAgger, and compare thei
CS285 Deep Reinforcement Learning HW3: Q-Learning and Actor-Critic Due: October 21st 2019, 11:59 pm 1 Part 1: Q-Learning 1.1 Introduction Part 1 of this assignment requires you to implement and evaluate Q-learning with convolutional neural networks for playing Atari games. The Q-learning algorithm was covered in lecture, and you will be provided with starter code. A GPU machine will be faster, but
https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/StudyCircleDeepReinforcementLearning/hw3.pdf - 2026-04-24
Study Circle in Reinforcement Learning Study Circle in Reinforcement Learning Coordinator: Karl-Erik Årzén Study Circle • A study circle and not a course • I know probably much less about RL than you do • Active participation Lectures and Meetings • The University College London (UCL) course ”Reinforcement Learning” by David Silver • 10 Video Lectures • Accompanying slides • Exercises • Code • Mee
https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/StudyCircleReinforcementLearning/Notes1.pdf - 2026-04-24
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REGLERTEKNIK LTH KURSINFORMATION NETWORK DYNAMICS FRTN30 (VT LP2, 7.5 hp) Why studying network dynamics? Networks permeate our modern societies. Everyday, we exchange information through the World Wide Web and other comminucation networks, modify our opinions and take decisions under the influence of our social interactions, commute across road networks, buy goods made available to us by productio
https://www.control.lth.se/fileadmin/control/Education/EngineeringProgram/FRTN30/FRTN30NetworkDynamics.pdf - 2026-04-24
19 August 2014 English version - November 2014 Instructions for a written critical review on degree projects at LTH The critical review (a peer review) is to be both oral and written and both parts are to be assessed by the examiner of the student defending the project (the respondent). The reviewer is responsible for providing a written review of the degree project to both the respondent and the
Microsoft Word - Teknisk rapportskrivning.doc In d u st ri a l E le c tr ic a l E n g in e e ri n g a n d A u to m a ti o n Teknisk rapportskrivning Gertrud Pettersson (Nordiska Språk) Gustaf Olsson (IEA) Mats Alaküla (IEA) Dept. of Industrial Electrical Engineering and Automation Lund University Innehåll Förord 2 1 Inledning 3 1.1 Syftet med denna skrift 3 1.2 Olika slag av skrivande 3 1.3 Hur ås
https://www.control.lth.se/fileadmin/control/Education/EngineeringProgram/FRTN45/2018/Teknisk_rapportskrivning.pdf - 2026-04-24
Mingle at the Lise Meitner seminar - LTH, Lunds Tekniska Högskola Mingle at the Lise Meitner seminar Erik Andersson (right), Research Coordinator at the Department of Design Sciences and the LTH Profile Area Aerosols. Photo: Kennet Ruona During the mingle following the Lise Meitner seminar 2025, we spoke to some of the participants about role models. Erik Andersson – Research Coordinator at the De
LTH:are spred kunskap om vikten av förebilder - LTH, Lunds Tekniska Högskola 2024-10-09, 15:52LTH:are spred kunskap om vikten av förebilder - LTH, Lunds Tekniska Högskola Page 1 of 4https://lthin.lth.lu.se/nyheter/lth-gemensamt/2024-10-09-lthare-spred-kunskap-om-vikten-av-forebilder.html LTH:are spred kunskap om vikten av förebilder Nyligen var Eva Westin, administrativ chef på Institutionen för r
https://www.control.lth.se/fileadmin/control/External_Engagement/LTHnews-20241009.pdf - 2026-04-24
