DOI: https://doi.org/10.15588/1607-3274-2020-4-19

IMPROVING THE ACCURACY OF AUTOMATIC CONTROL WITH MATHEMATICAL METER MODEL IN ON-BOARD CONTROLLER

S. M. Zinchenko, V. M. Mateichuk, P. S. Nosov, I. S. Popovych, E. S. Appazov

Abstract


Context. The article discusses the issues of increasing the accuracy of automatic control of a moving object using a mathematical model of a meter and a device observing measurement errors in the on-board controller of the control system. The object of the research is the processes of automatic control of a moving object with a mathematical model of a meter and a device observing measurement errors in the on-board controller of the control system. The subject of the research is a method and algorithms for increasing the accuracy of automatic control of a moving object with a mathematical model of a meter and a device observing measurement errors in the on-board controller of the control system.

Objective. The aim of research is an improving the accuracy of automatic control of a moving object.

Method. This aim is achieved through the use in the on-board controller of the control system of the mathematical meter model and the observing device built on its basis, the estimation of the useful component and the systematic error, depending on the motion parameters of the controlled object, using only the useful component for control, without systematic error.

Results. A method and algorithms for increasing the control accuracy of a moving object through the use in the on-board controller of a mathematical meter model and an observer of systematic measurement errors, built on its basis, have been developed. The efficiency and effectiveness of the developed method and algorithms were confirmed by mathematical modeling in the MATLAB environment of the control processes of a moving object in a closed circuit with a control system.

Conclusions. The results of mathematical modeling confirmed the operability and efficiency of the proposed method and algorithms and allow them to be used for practical purposes in the development of mathematical support for high – precision automatic control systems. 


Keywords


Аutomatic control, control accuracy, movement control systems, measurement errors, observing device, mathematical model.

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References


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GOST Style Citations


1. Using a MEMS gyroscope to measure the Earth’s rotation for gyrocompassing applications / L. I. Iozan, M. KirkkoJaakkola, J. Collin et al. // Measurement Science and Technology. – 2012. – Vol. 23, № 2. DOI: 10.1088/09570233/23/2/025005.

2. Error analysis and compensation of gyrocompass alignment for SINS on moving base / B. Xu, Y. Liu, W. Shan et al. // Mathematical Problems in Engineering. – 2014. DOI: 10.1155/2014/373575.

3. A Model-free Calibration Method of Inertial Navigation System and Doppler Sensors / B. Wang, J. Liu, Z. Deng et al. // IEEE Sensors Journal. – 2020. – P. 1558–1748. DOI: 10.1109/JSEN.2020.3015845.

4. Hu J. Estimation of azimuth gyro drifts with single-axis rotational SINS / J. Hu, Y. Zhu, X. Shi // Systems Engineering and Electronics. – 2018. – Vol. 40. – P. 2334– 2339. DOI: 10.3969/j.issn.1001-506X.2018.10.26

5. Luenberger D. G. An Introduction to Observer / D. G. Luenberger // IEEE Transactions on Automatic Control. – 1971. – P. 596–602.

6. Luders G. New Canonical Form for an Adaptive Observers / G. Luders, K. S. Narendra // IEEE Transactions on Automatic Control. – 1974. – P. 117–119.

7. Hostetter G. H. Observing Systems with Unmeasurable Inputs / G. H. Hostetter, J. S. Meditch // IEEE Transactions on Automatic Control. – 1973. – P. 307–308.

8. Kalman R. E. New results in linear filtering and prediction theory / R. E. Kalman, R. S. Busi // Journal of Basic Engineering. – 1961. – P. 95–108.

9. Improving Accuracy and Reliability in Automatic Ship Motion Control Systems / S. M. Zinchenko, A. P. Ben, P. S. Nosov et al. // Radio Electronics, Computer Science, Control. – 2020. – Vol. 2. – P. 183–195. DOI:10.15588/1607-3274-2020-2-19

10. Lee D. Application of neural-network for improving accuracy of roll-force model in hot-rolling mill / D. Lee, Y. Lee // Control Engineering Practice. – 2002. – Vol. 10, Issue 4. – P. 473–478. DOI: 10.1016/S0967-0661(01)00143-5.

11. Validation of a Mathematical Model for Road Cycling Power / J. Martin, D. Milliken, J. Cobb et al. // Journal of Applied Biomechanics. – Vol. 14, Issue 3. – P. 276–291. DOI: https://doi.org/10.1123/jab.14.3.276

12. Sutulo S. Mathematical models for ship path prediction in manoeuvring simulation systems / S. Sutulo, L. Moreira, C. Guedes Soares // Ocean Engineering. – 2002. – Vol. 29, Issue 1. – P. 1–19. DOI: 10.1016/S0029-8018(01)00023-3

13. Jikuang Y. Brain injury biomechanics in real world vehicle accident using mathematical models / Y. Jikuang, X. Wei, O. Dietmar // Chinese journal of mechanical engineering. – 2008. – Vol. 21, № 4. DOI: 10.3901/CJME.2008.04.081

14. Hydrodynamic parameter identification for ship manoeuvring mathematical models using a Bayesian approach / Y. Xue, Y. Liu, C. Ji et al. // Ocean Engineering. – 2020. – Vol. 195, Issue 1. DOI: 10.1016/j.oceaneng.2019.106612

15. Wada T. Analysis of driver’s head tilt using a mathematical model of motion sickness / T. Wada, S. Fujisawa, S. Doi // International Journal of Industrial Ergonomics. – 2018. – Vol. 63. – P. 89–97. DOI: 10.1016/j.ergon.2016.11.003

16. Comparative analysis of emotional personality traits of the students of maritime science majors caused by long-term staying at sea / R. Shevchenko, I. Popovych, L. Spytska et al. // Revista Inclusiones. – 2020. – Vol. 7. num Especial – P. 538–554.

17. Research of psychophysiological characteristics of response to stress situations by future sailors / R. Shevchenko, V. Cherniavskyi, S. Zinchenko et al. // Revista Inclusiones. – 2020. – Vol. 7. num Especial – P. 566–579.

18. Diagnostic system of perception of navigation danger when implementation complicated maneuvers / P. S. Nosov, S. M. Zinchenko, I. S. Popovych et al. // Radio Electronics, Computer Science, Control. – 2020. – Vol. 1. – P. 146–161. DOI: 10.15588/1607-3274-2020-1-15.

19. Development of means for experimental identification of navigator attention in ergatic systems of maritime transport / P. Nosov, I. Palamarchuk, S. Zinchenko et al. // Bulletin of University of Karaganda. Technical Physics. – 2020. – Vol. 1, Issue 97. – P. 58–69. DOI: 10.31489/2020Ph1/58-69.

20. Automatic collision avoidance with multiple targets, including maneuvering ones / S. M. Zinchenko, P. S. Nosov, V. M. Mateychuk et al. // Radio Electronics, Computer Science, Control. – 2019. – Vol. 4. – P. 211–221. DOI:10.15588/1607-3274-2019-4-20.

21. The vessel movement optimisation with excessive control / S. Zinchenko, A. Ben, P. Nosov et al. // Bulletin of University of Karaganda. Technical Physics. – 2020. – Vol. 3, No. 99. – P. 86–96, DOI: 10.31489/2020Ph3/86-96.

22. Bartley D. Diffusive Monitoring of Fluctuating Concentrations / D. Bartley, L. Doemeny, D. Taylor // American Industrial Hygiene Association Journal. – 1983. – Vol. 44, Issue 4. – P. 241–247. DOI: 10.1080/15298668391404734

23. Iwasa T. An Error Elimination Method for Surface Shape Measurement using the Grating Projection Method / T. Iwasa, M. Hiramatsu, N. Kishimoto et al. // Transactions of the Japan society for aeronautical and space sciences, aerospace technology Japan. – 2014. – Vol. 12. – P. 81–88. DOI: 10.2322/tastj.12.81

24. Zheng S. Simultaneous Temperature Compensation and Synchronous Error Elimination for Axial Displacement Sensors Using an Auxiliary Probe / S. Zheng, Y. Wang, H. Ren // IEEE Transactions on Industrial Electronics. – 2016. – Vol. 63, Issue 5. DOI: 10.1109/TIE.2015.2511165

25. Analysis and elimination the vibration disturbance in allfiber distributed polarization coupling measurement / G. Wen, H. Zhang, Y. Wang et al. // Measurement. – 2019. – Vol. 144. – P. 118–125. DOI: 10.1016/j.measurement.2019.05.033

26. The elimination of error of measurement of substance flow speed by the accounting of variation of its electrophysical parameters / I. V. Shirokov, S. N. Polivkin, Y. B. Gimpilevich et al. // IEEE Xplore. – 2009. DOI: 10.1109/EEEI.2008.4736573

27. M/T method based incremental encoder velocity measurement error analysis and self-adaptive error elimination algorithm / Y. Chen, M. Yang, J. Long et al. // Engineering, Computer Science. – 2017. DOI: 10.1109/IECON.2017.8216350

28. A study on systematic errors concerning rotor position estimation of PMSM based on back EMF voltage observation / P. Hutterer, H. Grabner, S. Silber et al. // IEEE Xplore. – 2009. DOI: 10.1109/IEMDC.2009.5075385

29. Quantifying and Reducing the DOA Estimation Error Resulting from Antenna Pattern Deviation for DirectionFinding HF Radar / Y. Lai, H. Zhou, Y. Zeng et al. // Remote Sensing. – Vol. 9, Issue 12. DOI: 10.3390/rs9121285







Copyright (c) 2020 S. M. Zinchenko, V. M. Mateichuk, P. S. Nosov, I. S. Popovych, E. S. Appazov

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