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Russian scientists created a neural network for adaptive shock absorbers

June 16, 2020

Motorists from all around the world were always interested in universal suspension: a suspension that will adapt to your driving conditions. 

However, the present suspension market offers an average product. This could change soon, though, as researchers from South Ural State University are developing an artificial neural network to improve the quality of adaptive shock absorbers.

This may sound futuristic but SUSU researchers have proposed a low-level controller based on Artificial Neural Networks with a built-in time delay for the shock absorber.  Yuri Rozhdestvensky, DSc, and his research team explained the use of an active shock absorber control based artificial network.

Their article, titled "Active Shock Absorber Control Based on Time-Delay Neural Network," is published in a special issue of Energies dedicated to intelligent transport systems. 

This will make future shockers more smooth and have greater handling and comfort, while contributing to traffic safety. Neural networks can adapt themselves to various changing variables, making them ideal for various fields like control systems. 

"An active shock absorber is a complex technical system with substantially nonlinear performance characteristics that have the property of hysteresis, a 'late response,' to changing conditions. The difficulty in controlling active shock absorbers lies in the fact that the same required values of forces can be achieved by actuators of various nature. So the shock absorber considered in the article has electromagnetic valves and a hydraulic pump, characterized by long response time. But with hydraulic pump control errors, the resulting system error can be significantly lower than with solenoid valves," says Yuri Rozhdestvensky