Lecture 1 - Introduction
Lecture 2 - Optimal Solution and Optimality Conditions
Lecture 3 - Convex Sets
Lecture 4 - Convex Functions
Lecture 5 - Convex Functions (Continued...)
Lecture 6 - Convex Optimization
Lecture 7 - Linear Programming
Lecture 8 - Linear Programming Duality
Lecture 9 - LP and Lagrangian Duality
Lecture 10 - Lagrangian Duality
Lecture 11 - Programming Demonstration
Lecture 12 - Programming Demonstration (Continued...)
Lecture 13 - Linear Matrix Inequalities
Lecture 14 - Linear Matrix Inequalities (Continued...)
Lecture 15 - Linear Matrix Inequalities
Lecture 16 - Dynamical Systems and Lyapunov Stability
Lecture 17 - Continuous-time LTI System
Lecture 18 - Lyapunov Stability and LMIs
Lecture 19 - D-Stability
Lecture 20 - Programming Demo
Lecture 21 - Controllability
Lecture 22 - State Feedback Control
Lecture 23 - Luenberger Observers
Lecture 24 - Analysis for Discrete-time Systems
Lecture 25 - Programming Demo
Lecture 26 - Programming Demo
Lecture 27 - Signal Norms
Lecture 28 - H_2 and H_Inf Spaces
Lecture 29 - LMIs for H_Inf Norm
Lecture 30 - H_Inf Optimal State Feedback Control
Lecture 31 - Programming Demo
Lecture 32 - H_2 Norm and LMIs
Lecture 33 - H_2 State Feedback Control and LQR
Lecture 34 - H_2 and H_Infinity Optimal Observer Design
Lecture 35 - Programming Demo.
Lecture 36 - Optimal Control Framework
Lecture 37 - Well-Posedness and Stability
Lecture 38 - Optimal Dynamic Output Feedback Control
Lecture 39 - Optimal Dynamic Output Feedback Control (Continued...)
Lecture 40 - Programming Demo
Lecture 41 - H-Infinity Norm for Discrete-Time LTI Systems
Lecture 42 - H-2 Norm for Discrete-Time LTI Systems
Lecture 43 - Stability Notions for Uncertain Systems
Lecture 44 - Quadratic Stability and State-Feedback Synthesis
Lecture 45 - Programming Demo
Lecture 46 - Dissipative Dynamical Systems
Lecture 47 - Dissipative LTI Systems and LMIs
Lecture 48 - Representing Uncertain Systems
Lecture 49 - Integral Quadratic Constraints
Lecture 50 - LMI for Robust L2 gain via IQC
Lecture 51 - IQCs for Discrete-Time Systems
Lecture 52 - Parametric Norm-Bounded Uncertainty
Lecture 53 - Programming Demo
Lecture 54 - Gradient-based Algorithms
Lecture 55 - Convergence of Gradient Descent
Lecture 56 - Convergence under Smoothness and Strong Convexity
Lecture 57 - Convergence under Smoothness and Strong Convexity (Continued...)
Lecture 58 - IQC and Programming Demo
Lecture 59 - IQC and Programming Demo
Lecture 60 - Concluding Remarks and Outlook
