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Structural Mechanics Department of Mechanics and Materials PER-ERIK AUSTRELL och MARTIN JÖNSSON ANALYS AV NÅGRA AXIALSYMMETRISKA GUMMIKOMPONENTER Rapport inom NUTEK-VAMP Denna sida skall vara tom! Copyright © 1999 by Structural Mechanics, LTH, Sweden. Printed by Universitetstryckeriet, Lund, Sweden. For information, address: Division of Structural Mechanics, LTH, Lund University, Box 118, SE-221 0

https://www.byggmek.lth.se/fileadmin/byggnadsmekanik/publications/tvsm7000/web7129.pdf - 2026-05-05

Structural Mechanics SIMON AICHER, PER JOHAN GUSTAFSSON (Editor), PEER HALLER and HANS PETERSSON FRACTURE MECHANICS MODELS FOR STRENGTH ANALYSIS OF TIMBER BEAMS WITH A HOLE OR A NOTCH - A Report of RILEM TC-133 Denna sida skall vara tom!

https://www.byggmek.lth.se/fileadmin/byggnadsmekanik/publications/tvsm7000/web7134.pdf - 2026-05-05

Microsoft Word - Rapport provningsresultat 2006 Part1 Ver2.doc Structural Mechanics Report TV SM -7149 PER JO H A N G U STA FSSO N TESTS O F FU LL SIZE R U B B ER FO IL A D H ESIV E JO IN TS PER JOHAN GUSTAFSSON TESTS OF FULL SIZE RUBBER FOIL ADHESIVE JOINTS Detta är en tom sida! Copyright © 2007 by Structural Mechanics, LTH, Sweden. Printed by KFS i Lund AB, Lund, Sweden, May 2007. For informatio

https://www.byggmek.lth.se/fileadmin/byggnadsmekanik/publications/tvsm7000/web7149.pdf - 2026-05-05

Adaptive Control Bo Bernhardsson and K. J. Åström Department of Automatic Control LTH, Lund University Bo Bernhardsson and K. J. Åström Adaptive Control Adaptive Control 1 Introduction 2 Model Reference Adaptive Control 3 Recursive Least Squares Estimation 4 The Self-Tuning Regulator 5 Real Adaptive Controllers 6 Summary Bo Bernhardsson and K. J. Åström Adaptive Control Introduction Adapt to adjus

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2016/AdaptiveControl.pdf - 2026-05-05

IQC toolbox IQC toolbox Gustav Nilsson May 25, 2016 IQC - Integral Quadratic Constraints • A unifying framework for systems analysis • Generalizes stability theorems such as small gain theorem and passivity theorem • Generalizes many concepts from robust control analysis • (Fairly) easy to build computer tools (convex optimization) Outline • Some theory on IQC • IQCβ toolbox • Live demo ICQ - Theo

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2016/GustavNilssonIQC.pdf - 2026-05-05

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https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2016/KTH_labmanual.pdf - 2026-05-05

() Pole Placement Design Bo Bernharsson and Karl Johan Åström Department of Automatic Control LTH, Lund University Bo Bernharsson and Karl Johan Åström Pole Placement Design Pole Placement Design 1 Introduction 2 Simple Examples 3 Polynomial Design 4 State Space Design 5 Robustness and Design Rules 6 Model Reduction 7 Oscillatory Systems 8 Summary Theme: Be aware where you place them! Bo Bernharss

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2016/PolePlacement.pdf - 2026-05-05

() Robust Control, H∞, ν and Glover-McFarlane Bo Bernharsson and Karl Johan Åström Department of Automatic Control LTH, Lund University Bo Bernharsson and Karl Johan Åström Robust Control, H∞, ν and Glover-McFarlane Robust Control 1 MIMO performance 2 Robustness and the H∞-norm 3 H∞-control 4 ν-gap metric 5 Glover-MacFarlane Theme: You get what you ask for! Bo Bernharsson and Karl Johan Åström Rob

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2016/Robust.pdf - 2026-05-05

ACC 1990 Benchmark Example References ACC 1990, pp. 961-962, The problem ACC 1990, pp. 963-973, Several Solutions ACC 1991, pp. 1931-1932, Mats Liljas design and comments The problem is to design a controller for a scalar linear system consisting of two-mass spring system. There are 4 states.

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2016/acc90.html - 2026-05-05

Aircraft dynamics with wind gust turbulence References Anderson and Moore p 222 The problem is to damp out the turbulence giving forward and aft acceleration on an aircraft. The model is of order 6. There is one input: rudder position. Matlab-code Model and code in fig822.m .

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2016/anderson222.html - 2026-05-05

ex02.dvi Exercise Session 2 1. Describe your results on Handin 1. 2. Sketch the Nichols curves for the following systems 1 s(s + 1)(s + 10) , 1 1 − s , exp (−s) 1 + s , 1 − s s(1 + s) , 1 s2 + 2ζs + 1 , (ζ small) For what feedback gains is the closed loop system stable? 3. Plot the root-loci for the following systems s s2 − 1 , (s + 1)2 s3 , 1 s(s2 + 2ζs + 1) , (ζ small) 4. Transform the systems i

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2016/ex02.pdf - 2026-05-05

ex4.dvi Exercise 4 Poleplacement and PID 1. Use Euclid’s algorithm to find all solutions to the equation 7x+ 5y = 6 where x and y are integers. 2. Use Euclid’s algorithm to find all solutions to the equation s2 x(s) + (0.5s+ 1)y(s) = 1 where x(s) and y(s) are polynomials. Use the results to find a solution to the equation s2 f (s) + (0.5s+ 1)(s) = (s2 + 2ζcω cs+ω2 c)(s 2 + 2ζoωos+ω2 o) such that t

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2016/ex4.pdf - 2026-05-05

ex6.dvi Exercise 6 LQG and H∞ 1. Use the appropriate Riccati equation to prove the Kalman filter identity R2 + C2(sI − A)−1 R1(−sI − AT)−1CT 2 = [Ip + C2(sI − A)−1 L]R2[Ip + C2(−sI − AT)−1 L]T Use duality to deduce the return difference formula Q2 + BT(−sI − AT)−1Q1(sI − A)−1B = [Im + K(−sI − AT)−1B]T Q2[Im + K(sI − A)−1B] 2. Consider the Doyle-Stein LTR example from the LQG lecture G(s) = s+ 2 (s

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2016/ex6.pdf - 2026-05-05

Extremum-seeking Control Extremum-seeking Control Tommi Nylander and Victor Millnert May 25, 2016 1 / 14 Short introduction I Non-model based real-time optimization I When limited knowledge of the system is available I E.g. a nonlinear equilibrium map with a local minimum I Popular around the middle of the 1950s I Revival with proof of stability 1 I Very attractive with the increasing complexity o

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2016/extremum-seeking-tommi-victor.pdf - 2026-05-05

() Gain Scheduling Bo Bernhardsson and Karl Johan Åström Department of Automatic Control LTH, Lund University Bo Bernhardsson and Karl Johan Åström Gain Scheduling Gain Scheduling What is gain scheduling ? How to find schedules ? Applications What can go wrong ? Some theoretical results LPV design via LMIs Conclusions To read: Leith & Leithead, Survey of Gain-Scheduling Analysis & Design To try ou

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2016/gainscheduling.pdf - 2026-05-05

() Handin 1 Bo Bernhardsson, K. J. Åström Department of Automatic Control LTH, Lund University Bo Bernhardsson, K. J. Åström Handin 1 Handin 1 - goals Get some practice using the Matlab control system toolbox (or similar) Get started with some control design Bo Bernhardsson, K. J. Åström Handin 1 Example - Double Integrator Consider the double integrator y = 1 s2 u controlled with state-feedback +

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2016/handin1.pdf - 2026-05-05

() Handin 3 Consider the (broomstick) system p2 s2 − p2 with p = 6 rad/s ((1 feet). Hint: You might find it useful to read or watch Gunter Stein’s Bode Lecture. a) Find a stabilizing controller achieving pT(iω)p < (Ωa/ω) 2, when ω > Ωa = 10 rad/s Ms := max ω pS(iω)p < 10 b) Try to get as low Ms you can, while maintaining the requirement on T. Bonus: Try to find a theoretical lower bound on Ms (the

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2016/handin3.pdf - 2026-05-05

handin5.dvi Handin 5 - Connected Inverted Pendulums (LQG) x1 x2 φ1 = x5 φ2 = x7 u1 u2 The process consists of two inverted pendulums mounted on movable carts. The carts are connected with a spring. The inputs are the forces on the two carts. The outputs are the cart positions and pendulum angles. The system hence have 2 inputs and 4 outputs. The system parameters correspond to 1m pendulums mounted

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2016/handin5.pdf - 2026-05-05

LQG-examples exkj2.m Slow process pole example fig822.m Aircraft turbulence attenuation lqg1.m An example where some eigenvalues are moved by LQG but some others are fixed. lqg2.m An example technical conditions are violated lqg3.m LTR example Doyle and Stein AC 79 exreducedobserver.m Reduced order design mac58.m LTR design example from Maciejowski at the end of lecture 10

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2016/lqg.html - 2026-05-05

Vertical Aerospace Dynamics, Maciejowski example 5.8 References Maciejowski pp. 244-258, Plots on LQGLTR designs Maciejowski pp. Appendix pp 405-406, Describes the model. Hung and MacFarlane, Multivariable Feedback: A quasi-classical Approach , Lecture Notes in Control and Information Sciences, vol 40, Springer-Verlag The problem is to control the vertical-plane dynamics of an aircraft. There are

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2016/mac58.html - 2026-05-05