Comments on “A computationally efficient technique for state estimation of nonlinear systems”. (English) Zbl 0795.93053
Summary: In a recent paper J. S. Dhingra, R. L. Moose, H. Vanlandingham and T. A. Lauzon [Automatica 28, No. 2, 395-399 (1992; Zbl 0767.93039)] have presented an estimation technique for a class of nonlinear systems. They claim to have shown by means of numerical examples that the proposed algorithm, called the Jump Matrix Technique (JMT), gave better results than the Extended Kalman Filter (EKF). The purpose of this note is to point out that a better implementation of the EKF would outperform the JMT.
MSC:
| 93C15 | Control/observation systems governed by ordinary differential equations |
| 93C10 | Nonlinear systems in control theory |
| 93C57 | Sampled-data control/observation systems |
Citations:
Zbl 0767.93039References:
| [1] | Gelb, A., (Applied Optimal Estimation (1974), MIT Press: MIT Press Cambridge, MA) |
| [2] | Dhingra, J. S.; Moose, R. L.; Vanlandingham, H.; Lauzon, T. A., A computationally efficient technique for state esimation of nonlinear systems, Automatica, 28, 395-399 (1992) · Zbl 0767.93039 |
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