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

## Authors

• S. M. Zinchenko Kherson State Maritime Academy
• V. M. Mateichuk Kherson State Maritime Academy
• P. S. Nosov Kherson State Maritime Academy
• I. S. Popovych Kherson State University
• E. S. Appazov Kherson State Maritime Academy

## Keywords:

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

## 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.

## Author Biographies

### S. M. Zinchenko, Kherson State Maritime Academy

PhD, Associate Professor of Ship Handling Department, Head of the Electronic Simulators Laboratory

### V. M. Mateichuk, Kherson State Maritime Academy

Senior Lecturer of Ship Handling Department, Head of the Electronic Simulators Laboratory

### P. S. Nosov, Kherson State Maritime Academy

PhD, Associate Professor of  Navigation Systems Department

### I. S. Popovych, Kherson State University

Dr. Sc., Professor of General and Social Psychology Department

### E. S. Appazov, Kherson State Maritime Academy

PhD, Associate Professor of Innovation Technology and Technical Tools of Navigation Department

## References

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

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

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

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

Luenberger D. G. An Introduction to Observer, IEEE Transactions on Automatic Control, 1971, pp. 596–602.

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

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

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

Zinchenko S. M., Ben A. P., Nosov P. S. et al. Improving Accuracy and Reliability in Automatic Ship Motion Control Systems, Radio Electronics, Computer Science, Control, 2020, Vol. 2, pp. 183–195. DOI:10.15588/1607-3274-20202-19

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

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

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

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

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

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

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

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

Nosov P. S., Zinchenko S. M., Popovych I. S. at al. Diagnostic system of perception of navigation danger when implementation complicated maneuvers, Radio Electronics,

Computer Science, Control, 2020, Vol. 1, pp. 146–161. DOI: 10.15588/1607-3274-2020-1-15.

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

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

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

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

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

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

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

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

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

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

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