View source for Supplement: Optimization-Based Control

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<font size="+1">[[User:Murray|Richard M. Murray]]</font>

These notes serve as a supplement to ''Feedback Systems'' by {{Astrom}} and Murray and expand on some of the topics introduced there.  Our focus is on the use of optimization-based methods for control, including optimal control theory, receding horizon control, and Kalman filtering.  Each chapter is intended to be a standalone reference for advanced topics that are introduced in ''Feedback Systems''.

'''Note:''' Permission is granted to download and print a copy for individual use, but this material may not be reproduced, in whole or in part, without written consent from the author.

===== News ([[OBC: Archived news|archive]]) =====
* Jan-Feb 2023: updated versions of Chapters 2-7 (version 2.3x) posted roughly every week
* 31 Dec 2022: posted Jupyter notebooks for Chapter 1 (intro to python-control)
* 29 Dec 2022: added new Chapter 1 (introduction) and starting to post updates for v2.3
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=== Contents ===
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* {{OBC pdf|Contents and Preface|obc-frontmatter|03Jan2023}}
* {{OBC pdf|Ch 1 - Introduction|obc-intro|03Jan2023}}
** System and Control Design
** The Control System “Standard Model”
** Layered Control Systems
** The Python Control Systems Library (python-control): {{OBC notebook|intro-iosys}}, {{OBC notebook|intro-xferfcn}}
** Exercises: {{OBC exercise|servomech-python_template.ipynb}}, {{OBC exercise|servomech.py}}
* {{OBC pdf|Ch 2 - Trajectory Generation and Tracking|obc-trajgen|08Jan2023}}
** Two Degree of Freedom Design
** Trajectory Tracking and Gain Scheduling
** Trajectory Generation and Differential Flatness
** Implementation in Python: {{OBC notebook|trajgen-gainsched}}, {{OBC notebook|trajgen-flatness}}
** Other Methods for Generating Trajectories
* {{OBC pdf|Ch 3 - Optimal Control|obc-optimal|14Jan2023}}
** Review: Optimization
** Optimal Control of Systems
** Examples
** Implementation in Python: {{OBC notebook|optimal-kincar}}, {{OBC python|kincar.py}}
** Linear Quadratic Regulators: {{OBC notebook|optimal-linquad}}, {{OBC notebook|optimal-pvtol-lqr}}, {{OBC python|pvtol.py}}
** Choosing LQR Weights
** Advanced Topics: {{OBC notebook|optimal-lqr-tracking}}
* {{OBC pdf|Ch 4 - Receding Horizon Control|obc-rhc|31Jan2022}}
** Optimization-Based Control
** Receding Horizon Control with Terminal Cost
** Implementation in Python
** Receding Horizon Control Using Differential Flatness
** Choosing Cost Functions
** Implementation on the Caltech Ducted Fan
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* {{OBC pdf|Ch 5 - Stochastic Systems|obc-stochastic|07Feb2022}}
** Review of Random Variables
** Introduction to Random Processes
** Continuous-Time, Vector-Valued Random Processes
** Linear Stochastic Systems
** Random Processes in the Frequency Domain
* {{OBC pdf|Ch 6 - Kalman Filtering|obc-kalman|13Feb2022}}
** Linear Quadratic Estimators
** Extensions of the Kalman Filter
** LQG Control
** Application to a Vectored Thrust Aircraft
* {{OBC pdf|Ch 7 - Sensor Fusion|obc-fusion|23Feb2022}}
** Discrete-Time Stochastic Systems
** Kalman Filters in Discrete Time
** Predictor-Corrector Form
** Sensor Fusion
** Information Filters
** Additional Topics
* {{OBC pdf|Bibliography and Index|obc-backmatter|03Jan2023}}
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