Robust Stochastic Design of Linear Controlled Systems for Performance Optimization
Abstract
This study discusses a robust controller synthesis methodology for linear, time invariant systems, under probabilistic parameter uncertainty. Optimization of probabilistic performance robustness for [script H]_2 and multi-objective [script H]_2 measures is investigated, as well as for performance measures based on first-passage system reliability. The control optimization approaches proposed here exploit recent advances in stochastic simulation techniques. The approach is illustrated for vibration response suppression of a civil structure. The results illustrate that, for problems with probabilistic uncertainty, the explicit optimization of probabilistic performance robustness can result in markedly different optimal feedback laws, as well as enhanced performance robustness, when compared to traditional "worst-case" notions of robust optimal control.
Additional Information
© 2010 American Society of Mechanical Engineers. Manuscript received November 5, 2009; final manuscript received May 3, 2010; published online August 19, 2010. Assoc. Editor: YangQuan Chen.Attached Files
Published - Taflanidis2010p11325Journal_Of_Dynamic_Systems_Measurement_And_Control-Transactions_Of_The_Asme.pdf
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Additional details
- Eprint ID
- 19949
- Resolver ID
- CaltechAUTHORS:20100914-113201336
- Created
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2010-09-15Created from EPrint's datestamp field
- Updated
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2021-11-08Created from EPrint's last_modified field