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 Spentzas | 1 | 2 | 1.43 |
Stratis A. Kanarachos | 2 | 2 | 1.09 |