Active Shock Absorber Control Based on Time-Delay Neural Network

Alexander Alyukov, Yuri Rozhdestvenskiy and Sergei Aliukov
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Alexander Alyukov: Automotive Engineering Department, South Ural State University, 454080 Chelyabinsk, Russia
Yuri Rozhdestvenskiy: Automotive Engineering Department, South Ural State University, 454080 Chelyabinsk, Russia
Sergei Aliukov: Automotive Engineering Department, South Ural State University, 454080 Chelyabinsk, Russia

Energies, 2020, vol. 13, issue 5, 1-16

Abstract: A controlled suspension usually consists of a high-level and a low-level controller. The purpose the high-level controller is to analyze external data on vehicle conditions and make decisions on the required value of the force on the shock absorber rod, while the purpose of the low-level controller is to ensure the implementation of the desired force value by controlling the actuators. Many works have focused on the design of high-level controllers of active suspensions, in which it is considered that the shock absorber can instantly and absolutely accurately implement a given control input. However, active shock absorbers are complex systems that have hysteresis. In addition, electro-pneumatic and hydraulic elements are often used in the design, which have a long response time and often low accuracy. The application of methods of control theory in such systems is often difficult due to the complexity of constructing their mathematical models. In this article, the authors propose an effective low-level controller for an active shock absorber based on a time-delay neural network. Neural networks in this case show good learning ability. The low-level controller is implemented in a simplified suspension model and the simulation results are presented for a number of typical cases.

Keywords: Active suspension; shock absorber; neural network; control (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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