Lecture 1 - Course Background: Model Predictive Control
Lecture 2 - Course Outline
Lecture 3 - Additional MATLAB Video - Array Operations
Lecture 4 - Additional MATLAB Video - Array Operations
Lecture 5 - Recap: Linear Algebra
Lecture 6 - Recap: Differential and Difference Equations
Lecture 7 - Recap: Process Control Basics
Lecture 8 - Introduction to Model Predictive Control
Lecture 9 - MPC: Salient Features
Lecture 10 - MPC: Historical Perspective
Lecture 11 - Vectors and Matrices
Lecture 12 - Vector Spaces
Lecture 13 - Linear Operation
Lecture 14 - Null and Image Spaces
Lecture 15 - Eigenvalues and Eigenvectors
Lecture 16 - Eigenvalue Decomposition and Tutorial
Lecture 17 - Recap of Week-2
Lecture 18 - Model Classification
Lecture 19 - Discrete-Time Models Overview
Lecture 20 - Discrete-Time Models
Lecture 21 - Finite Impulse Response Models
Lecture 22 - Finite Step Response Models
Lecture 23 - Recap and Plan for Week-4
Lecture 24 - State Space and Step Response Models
Lecture 25 - Nonlinear Models and Model Linearization
Lecture 26 - Model Types and Model Conversion
Lecture 27 - Model Conversion - 2
Lecture 28 - Model Conversion: TF to SS
Lecture 29 - How to handle MIMO systems
Lecture 30 - Discretization of State-Space Models
Lecture 31 - Introduction to Dynamic Matrix Control (DMC)
Lecture 32 - The DMC Algorithm: Future Predictions
Lecture 33 - The DMC Algorithm: Objective and Constraints
Lecture 34 - The DMC Algorithm: Optimization
Lecture 35 - Coding for DMC Algorithm: Setup
Lecture 36 - Coding for DMC Algorithm: Populate Matrices
Lecture 37 - Recap of DMC Algorithm
Lecture 38 - Extensions of DMC Algorithm
Lecture 39 - LTI Models and Coordinate Transform
Lecture 40 - LTI Models: Stability
Lecture 41 - LTI Models: Controllability
Lecture 42 - LTI Models: Conditions for controllability
Lecture 43 - Tutorial by Arvind (Recap of Controllability)
Lecture 44 - LTI Models: Observability
Lecture 45 - Linear Control: Introduction
Lecture 46 - Pole Placement Controller
Lecture 47 - Linear Quadratic Regulator: Batch Solution
Lecture 48 - LQR: Dynamic Programming Solution
Lecture 49 - State Estimation: Introduction
Lecture 50 - Stochastic Processes and Random Variables
Lecture 51 - State Estimation: Pole Placement Observer
Lecture 52 - Kalman Filter: Terminology
Lecture 53 - Kalman Filter: Derivation
Lecture 54 - Recap of Modules 7-9
Lecture 55 - Recap and Plan for this week
Lecture 56 - Linear Quadratic Gaussian
Lecture 57 - LQG Derivation and Separation Principle
Lecture 58 - Setpoint Tracking in LQ Control
Lecture 59 - Disturbance Rejection in LQ Control
Lecture 60 - Disturbance Modeling for Estimation
Lecture 61 - Estimation with Disturbance Modeling
Lecture 62 - Recap and Plan for this week
Lecture 63 - State-Space MPC: Deterministic case
Lecture 64 - Extension to Measured Disturbances
Lecture 65 - Offset-Free State Space MPC
Lecture 66 - Comparison of State-Space MPC with DMC
Lecture 67 - State-Space MPC: Disturbance Modeling
Lecture 68 - Disturbance Modeling: Background and Setup
Lecture 69 - Stochastic Output-Feedback State-Space MPC
Lecture 70 - Bonus Video: Disturbance Modeling for State Space MPC
Lecture 71 - Self-Guided Tutorial of MPC Toolbox
Lecture 72 - Help Session: Using MPC Toolbox
Lecture 73 - Recap of LQ Control and Linear MPC
Lecture 74 - Linear MPC - Key Features and Results
Lecture 75 - Practical Issues: Inferential Control
Lecture 76 - Practical Issues: Measurement Delay
Lecture 77 - Other Practical Issues
Lecture 78 - Some Classical Examples of MPC
