Introduction and Review of Basic Concepts |
Lecture 01 - Introduction, Motivation and Overview |
Lecture 02 - Overview of SS Approach and Matrix Theory |
Lecture 03 - Review of Numerical Methods |
Static Optimization |
Lecture 04 - An Overview of Static Optimization |
Lecture 05 - An Overview of Static Optimization (cont.) |
Optimal Control through Calculus of Variation |
Lecture 06 - Review of Calculus of Variations |
Lecture 07 - Review of Calculus of Variations (cont.) |
Lecture 08 - Optimal Control Formulation using Calculus of Variations |
Classical Numerical Techniques for Optimal Control |
Lecture 09 - Classical Numerical Methods to Solve Optimal Control Problems |
Linear Quadratic Regulator (LQR) Theory |
Lecture 10 - Linear Quadratic Regulator I |
Lecture 11 - Linear Quadratic Regulator II |
Lecture 12 - Linear Quadratic Regulator III |
Lecture 13 - Linear Quadratic Regulator IV |
Discrete Time Optimal Control |
Lecture 14 - Discrete Time Optimal Control |
Overview of Flight Dynamics |
Lecture 15 - Overview of Flight Dynamics I |
Lecture 16 - Overview of Flight Dynamics II |
Lecture 17 - Overview of Flight Dynamics III |
Optimal Missile Guidance |
Lecture 18 - Linear Optimal Missile Guidance using LQR |
State Dependent Riccati Equation and θ-D Designs |
Lecture 19 - SDRE and θ-D Designs |
Dynamic Programming and Adaptive Critic Design |
Lecture 20 - Dynamic Programming |
Lecture 21 - Approximate Dynamic Programming, Adaptive Critic and Single Network Adaptive Critic Design |
Advanced Numerical Techniques for Optimal Control |
Lecture 22 - Transcription Method to Solve Optimal Control Problems |
Lecture 23 - Model Predictive Static Programming and Optimal Guidance of Aerospace Vehicles |
Lecture 24 - Model Predictive Static Programming for Optimal Missile Guidance |
Lecture 25 - Model Predictive Spread Control and Generalized MPSR (G-MPSP) Designs |
Linear Quadratic Observer and Kalman Filter Design |
Lecture 26 - Linear Quadratic Observer and an Overview of State Estimation |
Lecture 27 - Review of Probability Theory and Random Variables |
Lecture 28 - Kalman Filter Design I |
Lecture 29 - Kalman Filter Design II |
Lecture 30 - Kalman Filter Design III |
Integrated Estimation, Guidance and Control |
Lecture 31 - Integrated Estimation, Guidance and Control |
Lecture 32 - Integrated Estimation, Guidance and Control (cont.) |
Linear Quadratic Gaussian Design |
Lecture 33 - LQG Design; Neighboring Optimal Controls and Sufficiency Condition |
Constrained Optimal Control |
Lecture 34 - Constrained Optimal Control I |
Lecture 35 - Constrained Optimal Control II |
Lecture 36 - Constrained Optimal Control III |
Optimal Control of Distributed Parameter Systems |
Lecture 37 - Optimal Control of Distributed Parameter Systems |
Lecture 38 - Optimal Control of Distributed Parameter Systems (cont.) |
Review and Summary |
Lecture 39 - Take Home Material: Summary |
Lecture 40 - Take Home Material: Summary (cont.) |