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ℋ2 optimal sensing architecture with model uncertainty | IEEE Conference Publication | IEEE Xplore

ℋ2 optimal sensing architecture with model uncertainty


Abstract:

In this paper we present an integrated approach to control and sensing design. The framework assumes sensor noise as a design variable along with the controller and deter...Show More

Abstract:

In this paper we present an integrated approach to control and sensing design. The framework assumes sensor noise as a design variable along with the controller and determines l1 regularized optimal sensing precision that satisfies a given closed loop performance in the presence of model uncertainty. We pursue two approaches here. In the first approach, we represent the uncertainty as polytopic and, in the second formulation, we model it using integral quadratic constraints (IQC). We apply these two approaches to an active suspension control and sensing design problem and demonstrate that the IQC based approach provides better results and is able to incorporate larger system uncertainty.
Date of Conference: 24-26 May 2017
Date Added to IEEE Xplore: 03 July 2017
ISBN Information:
Electronic ISSN: 2378-5861
Conference Location: Seattle, WA, USA

References

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