Difference between revisions of "Supplement: Optimization-Based Control"

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** Layered Control Systems
 
** Layered Control Systems
 
** The Python Control Systems Library (python-control)
 
** The Python Control Systems Library (python-control)
 +
*** {{OBC notebook|intro-iosys.ipynb|Introduction to python-control: Input/output Systems}}
 +
*** {{OBC notebook|intro-xferfcn.ipynb|Introduction to python-control: Transfer Functions}}
 
* {{OBC pdf|Ch 2 - Trajectory Generation and Tracking|obc-trajgen|08Jan2022}}
 
* {{OBC pdf|Ch 2 - Trajectory Generation and Tracking|obc-trajgen|08Jan2022}}
 
** Two Degree of Freedom Design
 
** Two Degree of Freedom Design

Revision as of 06:06, 31 December 2022

Quick Links

Richard M. Murray

These notes serve as a supplement to Feedback Systems by Åström 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: These notes are in draft form and may contain errors. 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 (archive)
  • Jan-Feb 2022: updated versions of Chapters 2-7 (version 2.2d) posted roughly every week
  • 21 Dec 2021: added new Chapter 1 (introduction) and starting to post updates for v2.2
  • 15 Feb 2010: updated version of Chapter 4 (stochastic systems) is posted; multiple fixes + some new material
  • 3 Jan 2010: posted updated version of Chapters 1 and 2 (mainly small fixes) + working errata link
  • 22 Dec 2009: updated versions of all chapters posted; working through small fixes over the next few weeks

Contents

  • Ch 5 - Stochastic Systems (PDF, 07 Feb 2022)
    • Review of Random Variables
    • Introduction to Random Processes
    • Continuous-Time, Vector-Valued Random Processes
    • Linear Stochastic Systems
    • Random Processes in the Frequency Domain
  • Ch 6 - Kalman Filtering (PDF, 13 Feb 2022)
    • Linear Quadratic Estimators
    • Extensions of the Kalman Filter
    • LQG Control
    • Application to a Vectored Thrust Aircraft
  • Ch 7 - Sensor Fusion (PDF, 23 Feb 2022)
    • Discrete-Time Stochastic Systems
    • Kalman Filters in Discrete Time
    • Predictor-Corrector Form
    • Sensor Fusion
    • Information Filters
    • Additional Topics
  • Bibliography and Index (PDF, 15 Feb 2010)