This course covers optimal control, guidance, and estimation techniques. By the end of the course, students will be able to formulate and solve optimal control problems, design linear quadratic regulators and observers, implement Kalman filters, and understand integrated estimation, guidance, and control systems. The course teaches skills such as static optimization, calculus of variations, numerical methods, dynamic programming, and model predictive control. The teaching method includes lectures on theoretical concepts, numerical methods, and real-world applications in aerospace and missile guidance systems. This course is intended for students and professionals interested in aerospace engineering, control systems, robotics, or autonomous systems.
Overview
Syllabus
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.
Taught by
aerospace engineering
