CDS 110b: State Estimation: Difference between revisions
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{{cds110b-wi08}} | {{cds110b-wi08 lecture|prev=Receding Horizon Control|next=Stochastic Systems}} | ||
This set of lectures presents an introduction to modern (optimization-based) control design and introduces the concepts of state estimation and observers. Beginning with a definition of observability, we provide conditions under which a linear system is observable and show how to construct an observer in the case where there is no noise. We then prove the ''separation principle'', which shows how to combine state regulation with state estimation. __NOTOC__ | This set of lectures presents an introduction to modern (optimization-based) control design and introduces the concepts of state estimation and observers. Beginning with a definition of observability, we provide conditions under which a linear system is observable and show how to construct an observer in the case where there is no noise. We then prove the ''separation principle'', which shows how to combine state regulation with state estimation. __NOTOC__ | ||
* {{cds110b-wi08 pdfs|L5- | * {{cds110b-wi08 pdfs|L5-1_estimators.pdf|Lecture Presentation}} | ||
== References and Further Reading == | == References and Further Reading == | ||
Latest revision as of 03:28, 2 March 2008
| CDS 110b | ← Schedule → | Project | Course Text |
This set of lectures presents an introduction to modern (optimization-based) control design and introduces the concepts of state estimation and observers. Beginning with a definition of observability, we provide conditions under which a linear system is observable and show how to construct an observer in the case where there is no noise. We then prove the separation principle, which shows how to combine state regulation with state estimation.
References and Further Reading
- K. J. Åström and R. M. Murray, Feedback Systems: An Introduction for Scientists and Engineers, Princeton University Press, 2008. Chapter 7 - Output Feedback. Sections 7.1-7.3
