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Reinforcement Learning: Machine Learning Meets Control Theory
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Classroom Contents
Control Bootcamp
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- 1 Control Bootcamp: Overview
- 2 Linear Systems [Control Bootcamp]
- 3 Stability and Eigenvalues [Control Bootcamp]
- 4 Linearizing Around a Fixed Point [Control Bootcamp]
- 5 Controllability [Control Bootcamp]
- 6 Controllability, Reachability, and Eigenvalue Placement [Control Bootcamp]
- 7 Controllability and the Discrete-Time Impulse Response [Control Bootcamp]
- 8 Degrees of Controllability and Gramians [Control Bootcamp]
- 9 Controllability and the PBH Test [Control Bootcamp]
- 10 Cayley-Hamilton Theorem [Control Bootcamp]
- 11 Reachability and Controllability with Cayley-Hamilton [Control Bootcamp]
- 12 Inverted Pendulum on a Cart [Control Bootcamp]
- 13 Pole Placement for the Inverted Pendulum on a Cart [Control Bootcamp]
- 14 Linear Quadratic Regulator (LQR) Control for the Inverted Pendulum on a Cart [Control Bootcamp]
- 15 Motivation for Full-State Estimation [Control Bootcamp]
- 16 Control Bootcamp: Observability
- 17 Control Bootcamp: Full-State Estimation
- 18 The Kalman Filter [Control Bootcamp]
- 19 Control Bootcamp: Observability Example in Matlab
- 20 Control Bootcamp: Observability Example in Matlab (Part 2)
- 21 Control Bootcamp: Kalman Filter Example in Matlab
- 22 Control Bootcamp: Linear Quadratic Gaussian (LQG)
- 23 Control Bootcamp: LQG Example in Matlab
- 24 Control Bootcamp: Introduction to Robust Control
- 25 Control Bootcamp: Three Equivalent Representations of Linear Systems
- 26 Control Bootcamp: Example Frequency Response (Bode Plot) for Spring-Mass-Damper
- 27 Control Bootcamp: Laplace Transforms and the Transfer Function
- 28 Control Bootcamp: Benefits of Feedback on Cruise Control Example
- 29 Control Bootcamp: Benefits of Feedback on Cruise Control Example (Part 2)
- 30 Control Bootcamp: Cruise Control Example with Proportional-Integral (PI) control
- 31 Control Bootcamp: Sensitivity and Complementary Sensitivity
- 32 Control Bootcamp: Sensitivity and Complementary Sensitivity (Part 2)
- 33 Control Bootcamp: Loop shaping
- 34 Control Bootcamp: Loop Shaping Example for Cruise Control
- 35 Control Bootcamp: Sensitivity and Robustness
- 36 Control Bootcamp: Limitations on Robustness
- 37 Control Bootcamp: Cautionary Tale About Inverting the Plant Dynamics
- 38 Control systems with non-minimum phase dynamics
- 39 Control Theory and COVID-19
- 40 Control Theory and COVID-19: Sensors
- 41 Control Theory and COVID-19: Summary
- 42 Control Theory and COVID-19: Models
- 43 Control Theory and COVID-19: Control Design
- 44 Reinforcement Learning: Machine Learning Meets Control Theory
- 45 Deep Reinforcement Learning: Neural Networks for Learning Control Laws
- 46 Model Predictive Control
- 47 Deep Reinforcement Learning for Fluid Dynamics and Control
