ESTIMATION OF UNMEASURABLE EXTERNAL DISTURBANCES OF A DYNAMIC OBJECT BASED ON A ROBUST ADAPTIVE KALMAN FILTER

Authors

• Bunyod Mamurjon ugli Buronov, Tashkent State Technical University named after Islam KarimovFollow

Abstract

This article considers the problem of directly estimating unmeasurable external disturbances acting on a dynamic object under the condition that the state vector of the object is available for measurement. In the considered case, the problem is reduced to the estimation of an unknown input of a dynamic system. It is shown that when the system state is measurable, both a direct inversion scheme based on the object’s dynamic equation and filtering methods that eliminate the need for coarse numerical differentiation can be applied. For slowly varying disturbances, a random walk model with a small process noise covariance is proposed, while for rapidly varying disturbances, an adaptive model with increased covariance and innovation-based signal adaptation is introduced. Issues of stability, robustness, regularization of ill-conditioned matrices, and practical applicability of the method are also discussed. Numerical examples for two cases are presented to illustrate the accuracy of external disturbance estimation.

First Page

64

Last Page

71

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Recommended Citation

Buronov, Bunyod Mamurjon ugli (2026) "ESTIMATION OF UNMEASURABLE EXTERNAL DISTURBANCES OF A DYNAMIC OBJECT BASED ON A ROBUST ADAPTIVE KALMAN FILTER," Technical science and innovation: Vol. 2026: Iss. 3, Article 11.
Available at: https://btstu.researchcommons.org/journal/vol2026/iss3/11