Inverse active vibration force inputs estimation for a beam–machine system

Abstract

This study presents an innovative fuzzy estimator that efficiently and robustly estimates the vibratory forces of a beam–machine system. The proposed estimator includes fuzzy Kalman filter technology, which is accelerated by the fuzzy accelerating factor and the fuzzy weighting recursive least-square method, weighted by the fuzzy weighting factor based on the fuzzy logic inference system. The excellent performance of this estimator is demonstrated by comparing it with different weighting functions, distinct levels of noise covariance measurement and the initial process noise covariance. The simulation results show that the proposed method is efficient in estimating input vibration forces, giving this method great stability and precision.

Keywords:

• fuzzy estimator
• fuzzy Kalman filter
• least-square method
• fuzzy logic

Acknowledgements

This research was partially supported by the National Science Council in Taiwan through Grant NSC 99-2221-E-145-003.