Neurocontrolled car speed system

• Autorzy: Nakonechnyi Markiyan , Ivakhiv Orest , Świsulski Dariusz

Identyfikatory

DOI

10.14313/JAMRIS/3-2022/20

• Języki publikacji: EN

Abstrakty

EN

The features of the synthesis of neural controllers for the car speed control system are considered in this article. The task of synthesis is to determine the weight coefficients of neural networks that provide the implementation of proportional and proportional-integralderivative control laws. The synthesis of controllers is based on an approach that uses a reversed model of the standard. A model of the car speed control system with the use of permitting subsystems has been developed, with the help of the synthesized controller that is connected under certain specified conditions. With the iterative programming and mathematical modeling environment in MATLAB, and using the Simulink package, a structural scheme for controlling the speed of the car was constructed and simulated using synthesized neural controllers.

Słowa kluczowe

EN

neural controller; PID-algorithm of control; dynamic object; neural networks; electric car; speed control

• Wydawca: Łukasiewicz Industrial Research Institute for Automation and Measurements PIAP
• Czasopismo: Journal of Automation Mobile Robotics and Intelligent Systems
• Rocznik: 2022
• Tom: Vol. 16, No. 3
• Strony: 13--21
• Opis fizyczny: Bibliogr. 41 poz., rys.

Twórcy

autor

Nakonechnyi Markiyan

• Computerized Automatic Systems Department, Computer Technology, Automation and Metrology Institute, Lviv Polytechnic National University, 12 Bandera str., Lviv 79013, Ukraine

autor

Ivakhiv Orest

• Intelligent Mechatronics and Robotics Department, Computer Technology, Automation and Metrology Institute, Lviv Polytechnic National University, 3 kn. Romana str., Lviv 79008, Ukraine

autor

Świsulski Dariusz

• Faculty of Electrical and Control Engineering, Gdańsk University of Technology, Gdańsk 80-233, Poland

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).