Learn · Convex Optimization in Control
Lecture 5 of 59Week 1
Lecture 05 : Convex Functions (Contd.)
Prof. Ashish Ranjan Hota · IIT Kharagpur
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All the lectures
- Lecture 01 : Introduction
- Lecture 02 : Optimal Solution and Optimality Conditions
- Lecture 03 : Convex Sets
- Lecture 04 : Convex Functions
- Lecture 05 : Convex Functions (Contd.)
- Lecture 06 : Convex Optimization
- Lecture 07 : Linear Programming
- Lecture 08 : Linear Programming Duality
- Lecture 09 : LP and Lagrangian Duality
- Lecture 10 : Lagrangian Duality
- Lecture 11 : Programming Demonstration
- Lecture 12 : : Programming Demonstration(Contd.)
- Lecture 13 : Linear Matrix Inequalities
- Lecture 14 : Linear Matrix Inequalities (Contd.)
- 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 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 Cont.
- 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 (Contd.)
- Lecture 58 : IQC and Programming Demo
- Lecture 59 : IQC and Programming Demo
- Lecture 60 : Concluding Remarks and Outlook