IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Use of the Neural Network Controller of Sprung Mass to Reduce Vibrations From Road Irregularities

Use of the Neural Network Controller of Sprung Mass to Reduce Vibrations From Road Irregularities
View Sample PDF
Author(s): Zakhid Godzhaev (Federal State Budgetary Scientific Institution “Federal Scientific Agroengineering Center VIM”, Russia), Sergey Senkevich (Federal State Budgetary Scientific Institution “Federal Scientific Agroengineering Center VIM”, Russia), Viktor Kuzmin (Federal State Budgetary Scientific Institution “Federal Scientific Agroengineering Center VIM”, Russia) and Izzet Melikov (Dagestan State Agricultural University Named After М.М. Dzhambulatov, Russia)
Copyright: 2021
Pages: 19
Source title: Research Advancements in Smart Technology, Optimization, and Renewable Energy
Source Author(s)/Editor(s): Pandian Vasant (University of Technology Petronas, Malaysia), Gerhard Weber (Poznan University of Technology, Poland) and Wonsiri Punurai (Mahidol University, Thailand)
DOI: 10.4018/978-1-7998-3970-5.ch005

Purchase

View Use of the Neural Network Controller of Sprung Mass to Reduce Vibrations From Road Irregularities on the publisher's website for pricing and purchasing information.

Abstract

Hydraulic systems that damp active oscillation operate according to a certain non-linear and time-varying algorithm. It is difficult to create a controller based on its dynamic model. This chapter proposes a new operation regime of the controller based on neuron nets by combining the advantages of the adaptive, radial, and basic functions of the neuron net. Its undoubted advantages are a learning (tilting) ability in real time to process indefinite, nonlinear disturbances, and to change the value of the active force in the hydraulic leaf spring by adjusting the weight coefficients of the neuron net and/or the radial parameters of the basic function. The model is a ¼ hydraulic active sprung mass of a mobile vehicle. The modeling shows that the use of a neuron net controller makes the sprung mass much more efficient.

Related Content

Junichiro Hayano, Emi Yuda. © 2021. 15 pages.
Anna Karagianni, Vasiliki Geropanta, Panagiotis Parthenios, Riccardo Porreca, Sofia Mavroudi, Antonios Vogiatzis, Lais-Ioanna Margiori, Christos Mpaknis, Eleutheria Papadosifou, Asimina Ioanna Sampani. © 2021. 21 pages.
Elias Munapo. © 2021. 16 pages.
Elias Munapo, Olusegun Sunday Ewemooje. © 2021. 16 pages.
Zakhid Godzhaev, Sergey Senkevich, Viktor Kuzmin, Izzet Melikov. © 2021. 19 pages.
Elias Munapo. © 2021. 22 pages.
Diriba Kajela Geleta, Mukhdeep Singh Manshahia. © 2021. 39 pages.
Body Bottom