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Optimal Control, Guidance and Estimation

Optimal Control, Guidance and Estimation. Instructor: Prof. Radhakant Padhi, Department of Aerospace Engineering, IISc Bangalore. In this course concepts and techniques of optimal guidance, control and state estimation will be studied for aerospace vehicles (especially for aircrafts, launch vehicles and missiles), both in linear and nonlinear systems theory framework. However, the theory as well as some demonstrative examples will be quite generic and hence this course is expected to be useful to the students from other engineering disciplines as well. (from nptel.ac.in)

Lecture 25 - Model Predictive Spread Control and Generalized MPSR (G-MPSP) Designs


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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.)