In this paper, we present an optimal filter for linear discrete-time stochastic systems with direct feedthrough that simultaneously estimates the states and unknown inputs in an unbiased minimum-variance sense. We argue that the information about the unknown input can be obtained from the current time step as well as the previous one, making it possible to estimate the unknown input in different ways. We then propose one variation of the filter that uses the updated state estimate to compute the best linear unbiased estimate (BLUE) of the unknown input. The comparison of the new filter and the filters in existing literature is discussed in detail and tested in simulation examples.
|Title of host publication
|2013 IEEE 52nd Annual Conference on Decision and Control, CDC 2013
|Institute of Electrical and Electronics Engineers Inc.
|Number of pages
|Published - 2013
|52nd IEEE Conference on Decision and Control, CDC 2013 - Florence, Italy
Duration: Dec 10 2013 → Dec 13 2013
|Proceedings of the IEEE Conference on Decision and Control
|52nd IEEE Conference on Decision and Control, CDC 2013
|12/10/13 → 12/13/13
ASJC Scopus subject areas
- Control and Systems Engineering
- Modeling and Simulation
- Control and Optimization