Sökresultat

Filtyp

Din sökning på "*" gav 541915 sökträffar

No title

LionSealWhite Linear Systems, 2019 - Lecture 4 Realization from Weighting Pattern Minimal Realizations Realization from Transfer Function Realization from Markov Parameters Discrete Time Rugh Ch 10, 11 (only pp194-199, skip proof of 11.7), (26) 1 / 30 LionSealWhite Example: Shift Register Synthesis x1 x2 x3 x4 x = [ x1 x2 x3 x4 ]T x(k + 1) =  1 0 0 1 1 0 0 0 0 1 0 0 0 0 1 0 x(k) + 

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/2019LinearSystem/2019_Linear_System_Lecture_4.pdf - 2025-09-30

No title

LionSealWhite Lecture 6 Least squares problems Adjoint operators 1 / 32 LionSealWhite Review: Least Squares Solution to Linear Equations (I) Consider a system of linear equations Ax = b, A ∈ Rm×n, b ∈ Rm with m ≥ n and rank(A) = n (Tall A—more rows than columns, or more equations than unknowns). If b /∈ range(A) then the linear system is inconsistent, i.e., no solution exists. Find x that minimize

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/2019LinearSystem/2019_Linear_System_Lecture_6.pdf - 2025-09-30

No title

LionSealWhite Lecture 8 Differential Algebraic Equations Rosenbrock System Matrix Course Review Suggested reading: T. Kailath Linear Systems, Chapter 8 (link available in the email). 1 / 26 LionSealWhite Differential Algebraic Equation Models of physical systems are often on the form 0 = F (ẋ, x, t) If x and ẋ enter linearly we get Eẋ = Ax+ f(t) Linear Differential Algebraic Equation (DAE) Any

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/2019LinearSystem/2019_Linear_System_Lecture_8.pdf - 2025-09-30

No title

6 LINEAR OPERATORS AND ADJOINTS 6.1 Introduction A study of linear operators and adjoints is essential for a sophisticated approach to many problems oflinear vector spaces. The associated concepts and notations of operator theory often streamline an otherwise cumber­ some analysis by eliminating the need for carrying along complicated explicit formulas and by enhancing one's insight of the problem

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/2019LinearSystem/Linear_operators_and_adjoints--David_G._Luenberger_-_Optimization_by_Vector_Space_Methods.pdf - 2025-09-30

No title

Adaptive Control K. J. Åström Department of Automatic Control, LTH Lund University October 23, 2020 Adaptive Control 1. Introduction 2. Self-oscillating Adaptive Control 3. Model Reference Adaptive Control 4. Estimation and Excitation 5. Minimum Variance Control 6. Self-Tuning Regulators 7. Learning and Dual Control 8. Applications 9. Related Fields 10. Summary Introduction Adapt to adjust to a sp

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2020/AdaptiveControleight.pdf - 2025-09-30

Control System Synthesis - Optimal control and LQG - PhD Class - Fall 2020

Control System Synthesis - Optimal control and LQG - PhD Class - Fall 2020 Control System Synthesis - Optimal control and LQG PHD CLASS - FALL 2020 The optimal control problem LQG control What is LQG control? Controllability and LQR Observability and state estimation Summary Optimal control Dynamic programming and HJB Indirect methods and Pontryagin’s principle Summary 1 Introduction 2 Fundamental

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2020/Control_System_Synthesis___LQG_and_optimal_control.pdf - 2025-09-30

Control System Synthesis - Robust control - PhD Class - Fall 2020

Control System Synthesis - Robust control - PhD Class - Fall 2020 Control System Synthesis - Robust control PHD CLASS - FALL 2020 Uncertainty and robustness Where does uncertainty come from? Modelling uncertainty Robustness Small gain theorem Robust stability Robust performance Robust synthesis H∞ -synthesis H∞ -Loopshaping synthesis µ-analysis and synthesis 1 Introduction 2 Fundamentals 3 Design

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2020/Control_System_Synthesis___Robust_control.pdf - 2025-09-30

Control System Synthesis - Data-driven control - PhD Class - Fall 2020

Control System Synthesis - Data-driven control - PhD Class - Fall 2020 Control System Synthesis - Data-driven control PHD CLASS - FALL 2020 Introduction to data-driven control The importance of data-driven approaches Model-based and data-driven control Overview of data-driven control technique Predictive and learning DDC Use of local models Use of repetitive experiments Robust DDC Using convex opt

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2020/Control_System_Synthesis___data_driven_control.pdf - 2025-09-30

No title

PID Control Karl Johan Åström Tore Hägglund Department of Automatic Control, Lund University September 23, 2020 PID Control 1. Introduction 2. The Controller 3. Stability 4. Performance and Robustness 5. Empirical Tuning Rules 6. Tuning based on Optimization 7. Relay Auto-tuning 8. Limitations of PID Control 9. Summary Theme: The most common controller. Introduction ◮ PID control is widely used in

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2020/PIDeight.pdf - 2025-09-30

No title

Control System Synthesis - PhD Class Exercise session 2 October 8, 2020 1 Inverted pendulum on a cart Figure 1: Inverted pendulum. The equations of motion are : (M +m)ẍ+ bẋ+mlθ̈ cos θ −mlθ̇2 sin θ = F (J +ml2)θ̈ +mgl sin θ = −mlẍ cos θ (1) where: • M = 0.5kg is the mass of the cart • m = 0.2kg is the mass of the pendulum • b = 0.1N/m/sec is the coefficient of friction for the cart • l = 0.3m is

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2020/PhD_Class___exercise_session_2.pdf - 2025-09-30

No title

Control System Synthesis - PhD Class Handin 1: Temperature control in a heat exchanger 24/09/2020 A chemical reactor called “stirring tank” is depicted below. The top inlet delivers liquid to be mixed in the tank. The tank liquid must be maintained at a constant temperature by varying the amount of steam supplied to the heat exchanger (bottom pipe) via its control valve. Variations in the temperat

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2020/PhD_Class___handin_1.pdf - 2025-09-30

flexservo.dvi

flexservo.dvi Handin - Flexible Servo The process consists of three horizontal pulleys connected by two elastic belts. SensorDC motor The transfer function from motor to sensor can take 3 forms (Ts = 50ms): Unloaded: B = 0.28261z−3 + 0.50666z−4 A = 1− 1.41833z−1 + 1.58939z−2 − 1.31608z−3 + 0.88642z−4 Half Load: B = 0.10276z−3 + 0.18123z−4 A = 1− 1.99185z−1 + 2.20265z−2 − 1.84083z−3 + 0.89413z−4 Fu

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/ControlSystemsSynthesis/2020/handin2.pdf - 2025-09-30

Deep-Learning Study Circle: Reinforcement Learning

Deep-Learning Study Circle: Reinforcement Learning Deep-Learning Study Circle: Reinforcement Learning Gabriel Ingesson 0/46 Reinforcement Learning The problem where an agent has to learn a policy (behavior) by taking actions in an environment, with the goal that the policy should maximize a cumulative reward. Different from supervised and unsupervised learning: No labeled training data. Reward sig

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/DeepLearning/2016/RL.pdf - 2025-09-30

Untitled

Untitled 1 History of Cont rol - Int roduc tion Karl Johan Åström Department of Automatic Control LTH Lund University Int roduc tion 1. Introduction 2. Practical Information 3. A Thumbnail History 4. The Power of Feedback 5. Summary Theme: Those who ignore history are doomed to repeat it. Those who cannot remember the past are condemned to repeat it. (George Santayana) Why bot her? ◮ Fun ◮ Useful

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/HistoryOfControl/2016/L01introductioneight.pdf - 2025-09-30

Untitled

Untitled 1 Process Cont rol Karl Johan Åström Department of Automatic Control LTH Lund University Process Cont rol K. J. Åström 1. Introduction 2. The Industrial Scene 3. Pneumatics 4. Theory? 5. Tuning 6. More Recent Development 7. Summary Theme: Measurement Control Instrumentation and Communication (pneumatic). Lectures 1940 1960 2000 1 Introduction 2 Governors | | | 3 Process Control | | | 4 Ae

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/HistoryOfControl/2016/L03ProcessControleight.pdf - 2025-09-30

L05ASMENyquistLecture.pdf

L05ASMENyquistLecture.pdf A S M E N y q u is t L e c tu re 2 0 0 5 N yq u is t an d H is S em in al P ap er s K ar l J o h an Å st rö m D ep ar tm en t o f M ec h an ic al E n g in ee ri n g U n iv er si ty o f C al if o rn ia S an ta B ar b ar a A S M E N y q u is t L e c tu re 2 0 0 5 H ar ry N yq u is t 18 89 -1 97 6 A G if te d S ci en ti st a n d E n g in ee r Jo h n so n -N yq u is t n o is

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/HistoryOfControl/2016/L05ASMENyquistLecturesix.pdf - 2025-09-30

()

() Automatic Control Emerges Karl Johan Åström Department of Automatic Control LTH Lund University Karl Johan Åström Automatic Control Emerges Automatic Control Emerges K. J. Åström 1 Introduction 2 The Computing Bottleneck 3 State of the Art around 1940 4 WWII 5 Servomechanisms 6 Summary Theme: Unification, theory, and analog computing. Karl Johan Åström Automatic Control Emerges Lectures 1940 19

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/HistoryOfControl/2016/L07ControlEmerges.pdf - 2025-09-30

Untitled

Untitled 1 Automatic Cont rol in Sweden Karl Johan Åström Department of Automatic Control, LTH Lund University Lectures 1940 1960 2000 1 Introduction 2 Governors | | | 3 Process Control | | | 4 Feedback Amplifiers | | | 5 Harry Nyquist | | | 6 Aerospace | | | 7 Automatic Control Emerges ← | | 8 The Second Phase ← ← | 9 Automatic Control in Sweden | | | 10 Automatic Control in Lund | | 11 The Futur

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/HistoryOfControl/2016/L09Swedeneight.pdf - 2025-09-30

L11Future.pdf

L11Future.pdf Some personal reflections The Future of Control K. J. Åström Department of Automatic Control LTH Lund University LTH April 24 2012 NAE, AFOSR, IEEE, IFAC LTH April 24 2012 The Systems Perspective In the past steady increases in knowledge has spawned new microdisciplines within engineering. However, contemporary challenges – from biomedical devices to complex manufacturing designs to

https://www.control.lth.se/fileadmin/control/Education/DoctorateProgram/HistoryOfControl/2016/L11Future_8.pdf - 2025-09-30