| 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.) |