Optimal Control, Guidance and Estimation

Delve into the comprehensive world of optimal control, guidance, and estimation in this extensive course. Explore fundamental concepts like state-space approach, matrix theory, and numerical methods before diving into static optimization and calculus of variations. Master the Linear Quadratic Regulator (LQR) and its applications in flight dynamics and missile guidance. Investigate advanced topics such as discrete-time optimal control, dynamic programming, and adaptive critic designs. Learn about transcription methods, Model Predictive Static Programming (MPSP), and their applications in aerospace vehicle guidance. Study state estimation techniques, including Kalman filter design and integrated estimation, guidance, and control systems. Examine constrained optimal control and the optimal control of distributed parameter systems. Gain practical knowledge through numerous lectures covering theoretical foundations and real-world applications in aerospace engineering and control systems.

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