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LionSealWhite Linear Systems, 2019 - Lecture 1 Introduction Multivariable Time-varying Systems Transition Matrices Controllability and Observability Realization Theory Stability Theory Linear Feedback Multivariable input/output descriptions Some Bonus Material 1 / 21 LionSealWhite Lecture 1 State equations Linearization Examples Transition matrices Rugh, chapters 1-4 Main news: Linearization aroun

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/2019LinearSystem/2019_Linear_System_Lecture_1.pdf - 2025-07-11

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LionSealWhite Lecture 5 LTV stability concepts Quadratic Lyapunov functions Feedback, Well-posedness, Internal Stability Rugh Ch 6,7,12 (skip proofs of 12.6 and 12.7),14 (pp240-247) + (22,23,24,28) Zhou, Doyle, Glover pp 117-124 1 / 31 LionSealWhite Stability For LTI systems ẋ = Ax the stability concept was easy, we had the two concepts i) Stability: x(t) remains bounded ii) Asymptotic stability:

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/2019LinearSystem/2019_Linear_System_Lecture_5.pdf - 2025-07-11

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LionSealWhite Lecture 7 Theory for polynomial matrices Hermite and Smith normal forms Smith McMillan form Poles and Zeros Rugh Ch 16-17 (can skip proofs of 16.7,17.4,17.5,17.6) 1 / 36 LionSealWhite Polynomial matrix fraction descriptions There are two natural generalisation to the SISO description G(s) = n(s) d(s) Right polyomial matrix fraction description: G(s) = NR(s)DR(s)−1 { DR(s)X(s) = U(s)

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/2019LinearSystem/2019_Linear_System_Lecture_7.pdf - 2025-07-11

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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

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/HistoryOfControl/2016/Bissell_history_of_automatic_control.pdf - 2025-07-11

Untitled

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 |

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/HistoryOfControl/2016/L10LundExperienceeight.pdf - 2025-07-11

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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

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/HistoryOfControl/2016/hoc_presentation_Marcus.pdf - 2025-07-11

History of Robotics

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

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/HistoryOfControl/2016/robot_control_pres_Martin.pdf - 2025-07-11

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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

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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

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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

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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

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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

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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

https://www.ht.lu.se/media/utbildning/dokument/kurser/HISA24/20252/HISA24_HISA34_Litteraturlista_Grundkurs_historia.pdf - 2025-07-11

Education

Education | Division of Physical Chemistry Faculty of Science Search Division of Physical Chemistry Department of Chemistry Department of Chemistry Kemicentrum Safety and security Contact About Education Master/Bachelor-Projects News and events Research People Instruments COMMONS Center Center for Scattering Methods Home  >  Education Denna sida på svenska This page in English Education  Undergrad

https://www.physchem.lu.se/education/news/commons/research/ - 2025-07-11