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Ships and Aerospace Karl Johan Åström Department of Automatic Control LTH Lund University Ships and Aerospace K. J. Åström 1. Introduction 2. A Little History 3. Sensing and actuation 4. Stability and Manoevrability 5. Autopilots 6. Dynamic Modeling Ships 7. Dynamic Modeling Aircrafts 8. Summary Ships and Aerospace ◮ Cutting edge technology ◮ Technology driver ◮ Driving forces: Emerging technologi

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/PhysicalModeling/Lectures/L06ShipsAndAerospaceeight.pdf - 2025-04-20

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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

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/PhysicalModeling/Lectures/L3-Methodologyeight.pdf - 2025-04-20

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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 - 2025-04-20

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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

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/PhysicalModeling/Lectures/L5-Mechanicaleight_01.pdf - 2025-04-20

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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

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/PhysicalModeling/Lectures/L6-FrictionModelseight.pdf - 2025-04-20

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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 - 2025-04-20

MTK for control

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 - 2025-04-20

Optimal Control of RLCT Networks

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

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/PhysicalModeling/Lectures/Richard_CircuitTheory.pdf - 2025-04-20

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FRTF05 Automatic Control Basic Course for F, I, Pi + TFRG95 Course Program Spring 2024 Updated Jan 9, 2024 1 Lectures The course consists of 15 lectures (30 hours). All lectures are held in M:A (Ole Römers väg 1). Lectures are held in Swedish. We will mainly use the whiteboard, but any additional materials such as compendia, exercises and lab manuals are available on Canvas. Schedule: See the we

https://www.control.lth.se/fileadmin/control/Education/EngineeringProgram/FRTF05/courseprogram2024FIPi.pdf - 2025-04-20

forskarutb.dvi

forskarutb.dvi FORSKARUTBILDNING I REGLERTEKNIK Varför forskarutbildning? Gillar Du kreativt arbete, där dina kunskaper och färdigheter får prövas på nya problemställningar? Vill Du kombinera frihet med ansvar? Uppskattar Du internationella kontakter och utlandsvistelser? Då är forskarutbildning något för Dig. Forskarutbildningens mål är att utveckla dokto- randens färdigheter i ett visst ämnesomr

https://www.control.lth.se/fileadmin/control/Education/EngineeringProgram/InformationSheets/2010-2011/forskarutb.pdf - 2025-04-20

FRT041ident.dvi

FRT041ident.dvi REGLERTEKNIK LTH KURSINFORMATION SYSTEMIDENTIFIERING FRT041 Vad är systemidentifiering? Identifiering och modellbygge behövs i tidiga faser av tekniskt och vetenskapligt arbete för att bestäm- ma empiriska beroenden mellan uppmätta variab- ler. Även om reglertekniska modeller har en cen- tral plats, innefattar därför tillämpningsområdena även experimentella och dataorienterade vete

https://www.control.lth.se/fileadmin/control/Education/EngineeringProgram/InformationSheets/2016-2017/FRT041ident.pdf - 2025-04-20

FRT090projektkurs.dvi

FRT090projektkurs.dvi REGLERTEKNIK LTH KURSINFORMATION PROJEKT I REGLERTEKNIK FRT090 Modellbaserad reglerdesign I ett industriellt reglerprojekt tar ofta modelle- ringsarbete en stor del av tiden. Det gäller också att beskriva de prestandabegränsingar som ges av dynamik i givare och ställdon och av mätbrus och styrsignalmättning. Kursprojekten genomförs före- trädesvis på verkliga modellprocesser

https://www.control.lth.se/fileadmin/control/Education/EngineeringProgram/InformationSheets/2016-2017/FRT090projektkurs.pdf - 2025-04-20

FRTN05olin.dvi

FRTN05olin.dvi REGLERTEKNIK LTH KURSINFORMATION OLINJÄR REGLERING OCH SERVOSYSTEM FRTN05 Vad är olinjär reglerteknik? Alla verkliga reglersystem är olinjära och man kommer ofta i kontakt med olinjära fysikaliska och tekniska fenomen såsom friktion, signalmättning etc. Ibland duger de linjära metoder som presenteras i våra andra kurser för att analysera och konstruera reglersystem även för olinjära

https://www.control.lth.se/fileadmin/control/Education/EngineeringProgram/InformationSheets/2016-2017/FRTN05olin.pdf - 2025-04-20

FRTN10flervar.dvi

FRTN10flervar.dvi REGLERTEKNIK LTH KURSINFORMATION FLERVARIABEL REGLERING FRTN10 Design av reglersystem Hur reglerar man en kemisk process, spårföljning- en i en DVD-spelare eller bränsleinsprutningen i en bil? Systemen är mycket olika, men har ändå många gemensamma drag. Ett sådant drag är att komplexa samband ökar behovet av systematiska verktyg för modellering och optimering. För att kla- ra de

https://www.control.lth.se/fileadmin/control/Education/EngineeringProgram/InformationSheets/2016-2017/FRTN10flervar.pdf - 2025-04-20

FRTN15predikt.dvi

FRTN15predikt.dvi REGLERTEKNIK LTH KURSINFORMATION PREDIKTIV REGLERING FRTN15 Vad är prediktiv reglering? Prediktion används inom reglerteknik och signal- behandling för att estimera framtida okända vär- den i en stokastisk process baserat på tidigare kän- da mätvärden. Modellbaserad prediktion (framför- hållning) med hjälp av en regulator-intern dyna- misk model av processen möjliggör därmed bätt

https://www.control.lth.se/fileadmin/control/Education/EngineeringProgram/InformationSheets/2016-2017/FRTN15predikt.pdf - 2025-04-20

No title

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/InformationSheets/2016-2017/FRTN30NetworkDynamics.pdf - 2025-04-20

Generate code for lasso problem

Generate code for lasso problem QPgen Home Examples Installation Documentation Licence Authors Citing Generate code for lasso problem % set problem dimensions q = 2000; n = 10000; % generate sparse data matrix F = sprandn(q,n,10/n); % regenerate until all columns are non zero while not(isempty(find(sum(F,2) == 0))) F = sprandn(q,n,10/n); end % store data in QP struct QP.H = F'*F; QP.G = F'; QP.C =

https://www.control.lth.se/fileadmin/control/Research/Tools/qpgen/gen_lasso.html - 2025-04-20

Help file for run_code_gen_MPC

Help file for run_code_gen_MPC QPgen Home Examples Installation Documentation Licence Authors Citing Help file for run_code_gen_MPC % ------------------------------------------------------- % [QP_reform,alg_data] = run_code_gen_MPC(MPC,opts) % Actions: % - reformulates MPC problem in struct MPC to QP problem in struct QP % - runs: run_code_gen(QP,opts) % -------------------------------------------

https://www.control.lth.se/fileadmin/control/Research/Tools/qpgen/help_run_code_gen_MPC.html - 2025-04-20

Simulate aircraft MPC system

Simulate aircraft MPC system QPgen Home Examples Installation Documentation Licence Authors Citing Simulate aircraft MPC system % nbr of time steps nbr_steps = 100; % create reference trajectory r_y1 = 0.25; r_y2 = 10; g1 = repmat(MPC.Q*[0;-r_y2;0;-r_y2],10,1); g1 = [g1;zeros(20,1)]; g2 = zeros(60,1); % time instance when reference is changed change_ref = 50; % initial condition X0 = zeros(4,1); %

https://www.control.lth.se/fileadmin/control/Research/Tools/qpgen/sim_aircraft_mpc.html - 2025-04-20

Pauline Kergus –

Pauline Kergus – Pauline Kergus Born November 25, 1992 H +33 (0)6 68 87 95 87 B pauline.kergus@control.lth.se Education 2016–2019 PhD in Automatic Control, ONERA, Toulouse, France. Supervision: Charles Poussot-Vassal and Fabrice Demourant. Title: "Data-driven model reference control in the frequency-domain: From model reference selection to controller validation." Thesis available at tel-3084374 2

https://www.control.lth.se/fileadmin/control/staff/PaulineKergus/CV_KERGUS.pdf - 2025-04-20