NDLI: A recursive state estimator in the presence of state inequality constraints

Content Provider	Springer Nature Link
Author	Hassan, Mohamed Fahim Zribi, Mohamed Alazemi, Hamed M. K.
Copyright Year	2011
Abstract	This paper proposes an optimal recursive estimator to estimate the states of a stochastic discrete time linear dynamic system when the states of the system are constrained with inequality constraints. The case when the constraints are strictly satisfied is treated independently from the case when some of the constraints are violated. For the first case, the well known Kalman filter estimator is used. In the second case, an algorithm which uses a series of successive orthogonalizations on the measurement subspaces is employed to obtain the optimal estimate. It is shown that the proposed estimator has several attractive properties such that it is an unbiased estimator. More importantly, compared to other estimator found in the literature, the proposed estimator needs less computational efforts, is numerically more stable and it leads to a smaller variance. To show the effectiveness of the proposed estimator, several simulation results are presented and discussed.
Starting Page	237
Ending Page	248
Page Count	12
File Format	PDF
ISSN	15986446
Journal	International Journal of Control, Automation and Systems
Volume Number	9
Issue Number	2
e-ISSN	20054092
Language	English
Publisher	Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers
Publisher Date	2011-04-02
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Inequality constraints Kalman filter recursive estimation Control Robotics Mechatronics
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Computer Science Applications

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