A Naive, Robust and Stable State Estimate

A naive approach to filtering for feedback control of dynamic systems that is robust and stable is proposed. Simulations are run on the filters presented to investigate the robustness properties of each filter. Each simulation with the comparison of the filters is carried out using the usual mean squared error. The filters to be included are the classic Kalman filter, Krein space Kalman, two adjustments to the Krein filter with input modeling and a second uncertainty parameter, a newly developed filter called the Naive filter, bias corrected Naive, exponentially weighted moving average (EWMA) Naive, and bias corrected EWMA Naive filter.

Name thesis:degree_name

MS

Grantor dc:publisher

Brigham Young University - Provo

Author dc:creator

• Remund, Todd Gordon

• Kalman
• Krein
• feedback control
• state estimation
• filter
• dynamic system
• robust state estimation
• robust
• EWMA
• bias correction
• Statistics and Probability

Language dc:language

English

Repository record dc:identifier

https://scholarsarchive.byu.edu/etd/1424

OAI identifier oai:identifier

oai:scholarsarchive.byu.edu:etd-2423