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Control System Synthesis - Model Predictive Control - PhD Class - Fall 2020 Control System Synthesis - Model Predictive Control PHD CLASS - FALL 2020 MPC design Basic idea How does MPC work? Design parameters Important issues Going further Robust MPC Stochastic MPC Running MPC faster and explicit MPC Adaptive and Gain-scheduled MPC Nonlinear MPC Data-driven MPC 1 Introduction 2 Fundamentals 3 Desi
DARC: Dynamic Adaptation of Real-time Control Systems DARC: Dynamic Adaptation of Realtime Control Systems Nils Vreman1, Claudio Mandrioli1 Control Systems Synthesis Project November 30, 2020 1{nils.vreman,claudio.mandrioli}@control.lth.se Dept. of Automatic Control Lund University { nils.vreman, claudio.mandrioli } @control.lth.se This story starts with... Vreman, Mandrioli DARC CSS Project 1
Neighborhood Heat Control Comfort Control and Peak Load Reduction Neighborhood Heat Control Comfort Control and Peak Load Reduction Felix Agner, Johan Lindberg November 30, 2020 Felix Agner, Johan Lindberg Neighborhood Heat Control November 30, 2020 1 / 13 Presentation Outline Problem: Control indoor temperature and peak electricity consumption in domestic buildings Problem formulation Results Dis
https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2020/Felix-JohanL.pdf - 2025-07-11
Control System Synthesis - PhD Class Exercise session 1 24/09/2020 1 The X-29 aircraft The X-29 aircraft has an unusual configuration, designed to enhance its maneuverability. It has a right half-plane pole at approximately p = 6rad/s and a right half-plane zero at z = 26rad/s. The non-minimum phase factor then writes: Pnmp(s) = z − s z + s s+ p s− p . What are the fundamental limitations ? 1. App
Deep Learning Tubes for Tube MPC Deep Learning Tubes for Tube MPC Johan Gronqvist Introduction MPC Tubes Three Problems Deep Learning Summary Deep Learning Tubes for Tube MPC Johan Gronqvist 2020-11-30 Deep Learning Tubes for Tube MPC Johan Gronqvist Introduction MPC Tubes Three Problems Deep Learning Summary Overview Contents I MPC I Tubes I Problems I Deep Learning I Summary Reference I Based on
https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2020/tubes-JohanG.pdf - 2025-07-11
1 A History of A4. A History of Automatic Control C.C. Bissell Automatic control, particularly the application of feedback, has been fundamental to the devel- opment of automation. Its origins lie in the level control, water clocks, and pneumatics/hydraulics of the ancient world. From the 17th century on- wards, systems were designed for temperature control, the mechanical control of mills, and th
Untitled 1 Automatic Cont rol in Lund Karl Johan Åström Department of Automatic Control, LTH Lund University Automatic Cont rol in Lund 1. Introduction 2. System Identification and Adaptive Control 3. Computer Aided Control Engineering 4. Relay Auto-tuning 5. Two Applications 6. Summary Theme: Building a New Department and Samples of Activities. Lectures 1940 1960 2000 1 Introduction 2 Governors |
A Brief History of Event-Based Control Marcus T. Andrén Department of Automatic Control Lund University Marcus T. Andrén A Brief History of Event-Based Control Concept of Event-Based Example with impulse control [Åström & Bernhardsson, 1999] Periodic Sampling Event-Based Sampling Event-Based: Trigger sampling and actuation based on signal property, e.g |x(t )| >δ (Lebesgue sampling) A.k.a aperiodi
History of Robotics History of Robotics Martin Karlsson Dept. Automatic Control, Lund University, Lund, Sweden November 25, 2016 Martin Karlsson November 30, 2016 1 / 14 Outline Introduction What is a robot? Early ideas The first robots Modern robots Major organizations Ubiquity of robots Future challenges Martin Karlsson November 30, 2016 2 / 14 Introduction The presenter performs research in rob
Lecture 3. The maximum principle In the last lecture, we learned calculus of variation (CoV). The key idea of CoV for the minimization problem min u∈U J(u) can be summarized as follows. 1) Assume u∗ is a minimizer, and choose a one-parameter variation uϵ s.t. u0 = u∗ and uϵ ∈ U for ϵ small. 2) The function ϵ 7→ J(uϵ) has a minimizer at ϵ = 0. Thus it satisfies the first and second order necessary
https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/Optimal_Control/2023/Lecture3.pdf - 2025-07-11
Exercise for Optimal control – Week 2 Choose one problem to solve. Exercise 1 (Insect control). Let w(t) and r(t) denote, respectively, the worker and reproductive population levels in a colony of insects, e.g. wasps. At any time t, 0 ≤ t ≤ T in the season the colony can devote a fraction u(t) of its effort to enlarging the worker force and the remaining fraction u(t) to producing reproductives. T
https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/Optimal_Control/2023/ex2.pdf - 2025-07-11
Exercise for Optimal control – Week 3 Choose 1.5 problems to solve. Disclaimer This is not a complete solution manual. For some of the exercises, we provide only partial answers, especially those involving numerical problems. If one is willing to use the solution manual, one should judge whether the solutions are correct or wrong by him/herself. Exercise 1. Consider a harmonic oscillator ẍ + x =
https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/Optimal_Control/2023/ex3-sol.pdf - 2025-07-11
Exercise for Optimal control – Week 6 Choose 1.5 problems to solve. Exercise 1. Derive the policy iteration scheme for the LQR problem min u(·) ∞∑ k=1 x⊤ k Qxk + u⊤ k Ruk with Q = Q⊤ ≥ 0 and R = R⊤ > 0 subject to: xk+1 = Axk +Buk. Assume the system is stabilizable. Start the iteration with a stabilizing policy. Run the policy iteration and value iteration on a computer for the following matrices:
https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/Optimal_Control/2023/ex6.pdf - 2025-07-11
7 Lecture 7. Dynamic programming II 7.1 Policy iteration In previous lecture, we studied dynamic programming for discrete time systems based on Bellman’s principle of optimality. We studied both finite horizon cost J = φ(xN ) + N−1∑ k=1 Lk(xk, uk), uk ∈ Uk and infinite horizon cost J = ∞∑ k=1 L(xk, uk), uk ∈ U(xk). The key ingredients we obtained were the Bellman equations. For finite horizon, J∗
https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/Optimal_Control/2023/lec7.pdf - 2025-07-11
Authors QPgen Home Examples Installation Documentation Licence Authors Citing Authors QPgen is developed and maintained by Pontus Giselsson . The development started during Pontus's postdoc studies at Stanford where he was advised by Prof. Stephen Boyd . Page generated 2015-12-09 10:07:10 CET, by jemdoc+MathJax .
https://www.control.lth.se/fileadmin/control/Research/Tools/qpgen/authors.html - 2025-07-11
Documentation QPgen Home Examples Installation Documentation Licence Authors Citing Documentation Documentation will be published here when ready. In the mean time, check out the examples or use the help command in MATLAB: >> help run_code_gen and >> help run_code_gen_MPC Page generated 2015-12-09 10:07:10 CET, by jemdoc+MathJax .
https://www.control.lth.se/fileadmin/control/Research/Tools/qpgen/documentation.html - 2025-07-11
Installation QPgen Home Examples Installation Documentation Licence Authors Citing Installation To install QPgen, follow the following simple guidelines: Download QPgen v0.0.2 ( release history ) Extract to path Run: make.m in MATLAB Add chosen path to MATLAB search path using the addpath command QPgen uses CVX , which is freely available, for some computations. QPgen does not hinge critically on
https://www.control.lth.se/fileadmin/control/Research/Tools/qpgen/installation.html - 2025-07-11
Publications | The Subject of History
https://www.hist.lu.se/en/research/publications/popularartiklar/1 - 2025-07-11
HIS A24, HISA34 Historia: Grundkurs 30 högskolepoäng Fastställd av institutionsstyrelsen 2017-12-01, reviderad 2019-11-08, 2022-03-25, 2022-11- 18, 2024-05-24 och 2025-06-08. Delkurs 1 Historia som vetenskap (7,5 högskolepoäng) Obligatorisk kurslitteratur Arnold, John, History. A Very Short Introduction, Oxford University press, Oxford, 2000 (137 s.)* Berglund, Louise och Ney, Agneta, Historikerns
