Title
Design of a non-linear hybrid car suspension system using neural networks
Abstract
A methodology for the design of active/hybrid car suspension systems with the goal to maximize passenger comfort (minimization of passenger acceleration) is presented. For this reason, a neural network (NN) controller is proposed, who corresponds to a Taylor series approximation of the (unknown) non-linear control function and the NN is due to the numerous local minima trained using a semi-stochastic parameter optimization method. Two cases A and B (continuous and discontinuous operation) are investigated and numerical examples illustrate the design methodology.
Year
DOI
Venue
2002
10.1016/S0378-4754(02)00029-0
Mathematics and Computers in Simulation
Keywords
Field
DocType
Hybrid car suspension,Neural networks,Semi-stochastic optimization
Linear approximation,Control theory,Mathematical optimization,Nonlinear system,Maxima and minima,Artificial neural network,Hybrid system,Stochastic programming,Mathematics,Taylor series
Journal
Volume
Issue
ISSN
60
3
0378-4754
Citations 
PageRank 
References 
2
1.09
1
Authors
2
Name
Order
Citations
PageRank
Konstantinos Spentzas121.43
Stratis A. Kanarachos221.09