Methodology for Model-Based Design of Mobile Robots Control Algorithms
https://doi.org/10.35596/1729-7648-2024-22-1-91-99
Abstract
This article proposes the formalized methodology for model-based design of mobile platform management systems. The methodology is based on an alternative approach to development, when the model of controlled object is firstly created as a design tool, and then control algorithms are developed. This allows to find the most successful algorithms and select control parameters that are close to optimal in the process of model-based design. As examples, two typical tasks from the field of mobile platform management are given - braking and steering control. The proposed methodology has sufficient unification to be used in the design of control systems for mobile platforms of various types, with different positioning systems, principles of navigation and autopiloting.
About the Authors
М. М. Tatur
Belarusian State University of Informatics and Radioelectronics
Russian Federation
Russian Federation
Tatur Mikhail Mikchailovich, Dr. of Sci. (Tech.), Professor, Professor at Electronic Computing Machines Department
220013, Minsk, P. Brovki St., 6
Tel.: +375 17 293-85-64
М. S. Ihnatsiuk
Belarusian State University of Informatics and Radioelectronics
Russian Federation
Russian Federation
Master Student at the Department of Information and Computer Systems Design
Minsk
А. D. Konikov
Belarusian State University of Informatics and Radioelectronics
Russian Federation
Russian Federation
Postgraduate at Electronic Computing Machines Department
Minsk
References
1. Timofeev A. N., Daeef F. (2021) Navigation of an Autonomous Mobile Robot Based on an Adaptive Neuro-Fuzzy Controller. Automation. Modern Technologies. (6), 268–272 (in Russian).
2. Tarasik V. P. (2019) Methodology for Simulation Testing of the Test Mode for Controllability and Stability of a Car When Entering a Turn. Bulletin of the Belarusian-Russian University. (2), 44–53 (in Russian).
3. Chi Zhang, Liangliang Yang, Ze Zhang (2013) Noboru Noguchi Development of Robot Tractor Associating with Human-drive Tractor for Farm Work. 5th IFAC Conference on Bio-Robotics. 46 (4), 83–88. https://doi.org/10.3182/20130327-3-JP-3017.00022.
4. State Standard GOST R 57700.37–2021. Computer Models and Simulation. Digital Twins of Products. General Provisions. Moscow, Russian Institute of Standardization (in Russian).
5. Tatur M., Lukashevich M., Shaverdo M. (2018) Training Task of Modeling the Braking Control System of a Mobile Robotic Platform. Space Engineering, Technologies & Exploration Anthology of Scientific Research Papers: Applied Curricula in Space Exploration and Intelligent Robotic Systems. Berlin. 109–115.
6. Zhartybayeva M. G., Tatur M. M., Shaverdo M. M., Iskakov K. T. (2019) Method of Reducing the Computational Complexity of Fuzzy Inference Algorithms for Implementation on a Microcontroller with Limited Computational Resources. Eurasian Journal of Mathematical and Computer Applications. 7 (1), 65–78.
7. Gerdts M. (2005) Solving Mixed-Integer Optimal Control Problems by Branch&Bound: A Case Study from Automobile Test-Driving with Gear Shift. Optimal Control Applications and Methods. (26), 1–18.
8. Stepanov D. N., Smirnova E. Yu. (2017) Method for Correcting the Assessment of the Position of a Mobile Robot Using Visual Location of Natural Landmarks. Mechatronics, Automation, Control. 18 (11), 752–757. DOI: 10.17587/mau.18.752-757 (in Russian).
9. Zenkevich S. L., Hua Zhu (2017) Control of the Movement of a Group of Robots in a “Convoy” Formation. Mechatronics, Automation, Control. 18 (1), 30–34. DOI: 10.17587/mau.18.30-34 (in Russian).
10. Belevich A. V., Lutsky V. I., Odinets D. N., Tatur M. M., Nguyen Trung Tin, Duong Quoc Hoang (2013) Modeling Control Algorithms for Automatic Transmissions to Ensure Smooth Gear Shifting. Neurocomputers: Development, Application. Radio Engineering. (2), 40–44 (in Russian).
Review
For citations:
Tatur М.М., Ihnatsiuk М.S., Konikov А.D. Methodology for Model-Based Design of Mobile Robots Control Algorithms. Doklady BGUIR. 2024;22(1):91-99. (In Russ.) https://doi.org/10.35596/1729-7648-2024-22-1-91-99
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