obc-frontmatter_03Jan10

obc-frontmatter_03Jan10 - Optimization-Based Control...

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Optimization-Based Control Richard M. Murray Control and Dynamical Systems California Institute of Technology DRAFT v2.1a, January 3, 2010 c ± California Institute of Technology All rights reserved. This manuscript is for review purposes only and may not be reproduced, in whole or in part, without written consent from the author.
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Preface These notes serve as a supplement to Feedback Systems by ˚ Astr¨ om and Murray and expand on some of the topics introduced there. They are motivated by the increasing role of online optimization in feedback systems. This is a change from the traditional use of optimization in control theory for ofine design of control laws and state estimators. Fueled by Moore’s law and improvements in real-time algorithms, it is now possible to perform estimation and control design algorithms online, allowing the system to better account for nonlinearities and to adapt to changes in the underlying dynamics of the controlled process. This changes the way that we think about estimation and control since it allows much greater ±exibility in the design process and more modularity and ±exibility in the overall system. Our goal in this supplement is to introduce the keys formalisms and tools re- quired to design optimization-based controllers. Key topics include real-time tra- jectory generation using di²erential ±atness, the maximum principle, dynamic pro- gramming, receding horizon optimal control, stochastic processes, Kalman ³ltering, moving horizon estimation and (distributed) sensor fusion. While these topics might normal consititute separate textbooks, in this set of notes we attempt to present
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obc-frontmatter_03Jan10 - Optimization-Based Control...

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