Dynamic shape estimation using Kalman filtering

Peter S. Lively; Mauro J. Atalla; Nesbitt W. Hagood

doi:10.1117/12.388854

22 June 2000 Dynamic shape estimation using Kalman filtering

Peter S. Lively, Mauro J. Atalla, Nesbitt W. Hagood

Author Affiliations +

Proceedings Volume 3985, Smart Structures and Materials 2000: Smart Structures and Integrated Systems; (2000) https://doi.org/10.1117/12.388854
Event: SPIE's 7th Annual International Symposium on Smart Structures and Materials, 2000, Newport Beach, CA, United States

Abstract

This paper proposes the use of a modern control method, the Kalman filter, to perform dynamic shape estimation of structures. Existing dynamic shape estimation techniques use static estimation techniques at each time step. This approach has been shown to be unsatisfactory, since aliasing of the higher modes, which is largely not seen in the static case, occurs strongly in the dynamic case. In many cases the aliasing produces signal to noise ratios significantly greater than unity. The proposed approach uses a Kalman filter to sift out the desired low frequency modes, since they contribute the most to the displacements, and treats the higher modes as a component of the noise in the system. Also, unlike the static techniques, the Kalman filter allows sensing of a number of modes larger than the number of sensors, and it takes into account the measurement errors. Numerical simulations show that the Kalman filtering technique can reduce the error from a thousand percent down to less than a percent for an ideal cantilever beam. Experimental data, susceptible to modeling and sensing errors, show that the proposed method results in a significant improvement over existing techniques.

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Peter S. Lively, Mauro J. Atalla, and Nesbitt W. Hagood "Dynamic shape estimation using Kalman filtering", Proc. SPIE 3985, Smart Structures and Materials 2000: Smart Structures and Integrated Systems, (22 June 2000); https://doi.org/10.1117/12.388854

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