Optimal Control, Guidance and Estimation

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2 STUDENTS

Introduction and Review of Basic Concepts : Introduction, Motivation and Overview – Overview of SS Approach and Matrix Theory – Review of Numerical Methods – Static Optimization : An Overview of Static Optimization – Optimal Control through Calculus of Variation :Review of Calculus of Variations – Optimal Control Formulation Using Calculus of Variations – Classical Numerical Methods to Solve Optimal Control Problems – Linear Quadratic Regulator (LQR) Theory – Discrete-time Optimal Control – Overview of Flight Dynamics – Optimal Missile Guidance : Linear Optimal Missile Guidance using LQR – State Dependent Riccati Equation and θ – D Designs – Dynamic Programming and Adaptive Critic Design : Dynamic Programming – Approximate Dynamic Programming (ADP), Adaptive Critic (AC) and Single – Network Adaptive Critic (SNAC) Design

Advanced Numerical Techniques for Optimal Control : Transcription Method to Solve Optimal Control Problems – Model Predictive Static Programming (MPSP) and Optimal Guidance of Aerospace Vehicles – MPSP for Optimal Missile Guidance – Model Predictive Spread Control (MPSC) and Generalized MPSP (G-MPSP) Designs – LQ Observer and Kalman Filter Design : Linear Quadratic Observer & An Overview of State Estimation – Review of Probability Theory and Random Variables – Kalman Filter Design – Integrated Estimation, Guidance and Control – Linear Quadratic Guassian Design : LQG Design; Neighboring Optimal Control& Sufficiency Condition – Constrained Optimal Control – Optimal Control of Distributed Parameter System – Review and Summary : Take Home Material: Summary

Course Curriculum

Introduction, Motivation and Overview Details 58:51
Overview of SS Approach and Matrix Theory Details 58:5
Review of Numerical Methods Details 58:45
An Overview of Static Optimization — I Details 56:14
An Overview of Static Optimization — II Details 58:57
Review of Calculus of Variations — I Details 59:2
Review of Calculus of Variations — II Details 59:40
Optimal Control Formulation Using Calculus of Variations Details 1:24
Classical Numerical Methods to Solve Optimal Control Problems Details 57:2
Linear Quadratic Regulator (LQR) — I Details 52:59
Linear Quadratic Regulator (LQR) — II Details 56:27
Linear Quadratic Regulator (LQR) — III Details 59:29
Linear Quadratic Regulator (LQR) — III Details 55:34
Discrete-time Optimal Control Details 55:29
Overview of Flight Dynamics — I Details 54:33
Overview of Flight Dynamics — II Details 59:52
Overview of Flight Dynamics — III Details 58:53
Linear Optimal Missile Guidance using LQR Details 1:2:5
SDRE and θ — D Designs Details 1:11
Dynamic Programming Details 58:41
Approximate Dynamic Progr (ADP),Adaptive Critic (AC) Details 1:6
Transcription Method to Solve Optimal Control Problems Details 59:43
Model Predictive Static Programming (MPSP) and Optimal Guidance of Aerospace Vehicles Details 1:14
MPSP for Optimal Missile Guidance Details 1:1:39
Model Predictive Spread Control (MPSC) and Generalized MPSP (G-MPSP) Designs Details 57:10
Linear Quadratic Observer & An Overview of State Estimation Details 53:24
Review of Probability Theory and Random Variables Details 57:35
Kalman Filter Design — I Details 53:14
Kalman Filter Design — II Details 49:58
Kalman Filter Design — III Details 59:47
Integrated Estimation, Guidance & Control — I Details 1:1:45
Integrated Estimation, Guidance & Control — II Details 1:7
LQG Design; Neighboring Optimal Control & Sufficiency Condition Details 55:45
Constrained Optimal Control — I Details 58:15
Constrained Optimal Control — II Details 59:18
Constrained Optimal Control — III Details 55:23
Optimal Control of Distributed Parameter Systems — I Details 57:4
Optimal Control of Distributed Parameter Systems — II Details 54:24
Take Home Material: Summary — I Details 57:13
Take Home Material: Summary — I Details 1:2:11

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