The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Motor vehicle accidents are one of the main killers on the road. Modern vehicles have several safety features to improve the stability and controllability. The tire condition is critical to the proper function of the designed safety features. Under or over inflated tires adversely affects the stability of vehicles. It is generally the vehicle's user responsibility to ensure the tire inflation pressure...
A novel compound controller is developed for the vehicle active suspension with an electro-hydraulic actuator. The models of the actuator and the quarter vehicle are both first established. A compound controller is designed to utilize RBF neural network approximate the output of PID, and to combine PID algorithm with a RBF neural network output as its control laws. This controller synthesizes both...
In this paper, a six degree of freedom half body vehicle suspension system is developed. The neural network algorithm is used to control the suspension system. With the aid of software Matlab/Simulink, the simulation model is achieved. With changing of neural network coefficients, such as changing of training epoch and changing of the network structure, a lot of simulation work is done. Simulation...
Artificial neural networks are used to estimate side slip angle and yaw rate of a vehicle's lateral dynamics. The networks are adapted to varying operating conditions such as a shift in vehicle weight, a change in road surface, and a radical change in tire characteristics. The structure and characteristics of the networks used are detailed. The methods for both offline and online training are described...
An active suspension system for vehicles using the genetic algorithms and neural network controls strategy is presented. A half car four degree of freedom suspension vibration model is described. Compared with the conventional passive suspension system, the analysis is done to the system control performance. The analysis of the system response is obtained through the change of the neural network training...
Neural Network-adaptive Control Algorithm is pointed out according to the non-linear characteristic for the semi-active suspension of automobiles and at the same time the recognition device and controller have been designed.The results of the simulation research on the 1/4 variable rigidity air suspension show that neural network self- adaptive controlled semi-active air suspension has an apparent...
This paper proposes a new method for automatically detecting the states of the road surface from tire noises of vehicles. The methods are based on a fast Fourier transform analysis, an artificial neural network, and the mathematical theory of evidence. The proposed classification is carried out in sets of multiple neural networks using the learning vector quantization networks. The outcomes of the...
A method for identification of adjustable shock absorbers is presented which combines a modern QRRLS parameter estimation algorithm (DSFI) with an artificial neural network (ANN) for classification purposes. The parameter estimation algorithm is based on a discrete-time linear model. Thus, no state variable filter (SVF) as for continuous time identification problems is required. For the ANN, a multilayer...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.