Stepwise fuzzy correction of the algorithm filters of random signals
https://doi.org/10.21122/2309-4923-2019-1-35-40
Abstract
The task of estimating the information contained in random signals from various sources – meters. It is assumed that the gauges are discrete and are described, like the original process assessed, by a discrete mathematical model in the form of difference equations. As an estimation algorithm, we consider a discrete Kalman filter, which, in the general case, when mathematical models are inadequate to real processes, can give distorted information. To improve the accuracy of estimation, it is proposed to apply the integration of all possible meters with the introduction of additional a priori information using a fuzzy logic system. At the same time, it is proposed to make a transition from the obtained probability characteristics of the estimated process to the membership functions of fuzzy logic based on the output filter parameters using the normalization of the posterior probability density. This approach allows to increase the accuracy of estimation, as it takes into account additional information and its complex processing.
About the Authors
A. A. Lobaty
Belarusian National Technical University
Belarus
Doctor of Science, Professor
Belarus
Doctor of Science, Professor
A. S. Radkevich
Belarusian National Technical University
Belarus
Post-graduate student
Belarus
Post-graduate student
References
1. Pugachev, V. S. Theory of stochastic systems / V. S. Pugachev, I. N. Sinitsyn. – Moscow: Logos, 2004. – 1000 p.
2. Methods of classical and modern theory of automatic control: 5 t. / Ed. K. A. Pupkova and N. D. Egupova. – M.: Publishing House MSTU. N. E. Bauman, 2004. – 5 tons.
3. Yarushkina, N. G. Fundamentals of the theory of fuzzy and hybrid systems / N. G. Yarushkina. – M: Economy and Finance, 2004. – 320 p.
4. Balakrishnan, A. V. Kalman filtering theory: Per. from English. / A. V. Balakrishnan. – Moscow: Mir, 1988. – 168 p.
5. Sinitsyn, I. N. Kalman filters and Pugachev / I. N. Sinitsyn. – M: University Book, 2006. – 640 p.
6. Lobaty, A. A. Optimal Estimation of random processes on the criterion of maximum a posteriori probability / A. A. Lobaty, Y. F. Yatsyna, N. N. Arefiev // Systems Analysis and Applied Informatics. – 2016. – № 1. – pp 35–41.
7. Lobaty, A. A. Fuzzification signals nonlinear stochastic system / A. A. Lobaty, M. A. Al-Mashhadani // Bulletin of National Technical University. – 2013. – № 2. – S. 28–32.
8. Lobaty, A. A. Structural-parametric correction fuzzy fi algorithm / A. A. Lobaty, A. S. Abufanas, A. S. Benkafo // Systems Analysis and Applied Informatics. – 2014. – № 4. – pp 4–8.
9. Orientation and navigation of mobile objects: modern information soc / ed. BS Aleshin, KK Veremeyenko, AI Black Sea. – M: FIZMATLIT, 2006. – 424 p.
10. Lobaty, A. A. Features The use of filters in the Kalman-Bucy complexes orientation and navigation / A. A. Lobaty, A. S. Benkafo // report BSUIR 2013 № 5 (75), pp 67–71.
Review
For citations:
Lobaty A.A., Radkevich A.S. Stepwise fuzzy correction of the algorithm filters of random signals. «System analysis and applied information science». 2019;(1):35-40. (In Russ.) https://doi.org/10.21122/2309-4923-2019-1-35-40
Views:
755
Email this article 