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Abstract: The nonlinear dynamic model of automotive semi-active
suspension is established with considering of the nonlinear
characteristics of the MR (Magnetorhelogical) damper and the nonlinear
rigidity of springiness element. At first, the non-linear control
strategy of differential geometry theory is applied to execute feedback
control on the semi-active suspension. The nonlinear model of the
semi-active suspension is transferred to a simple linear system through
a nonlinear state feedback. Then, according to the road excitation, the
predetermined control object and the fuzzy control strategy to adjust
the fuzzy logic control parameters, the fuzzy controller is designed.
Furthermore, the neural network controllers are designed to improve
automotive ride comfort. Finally, the simulation results are made a
comparison between three non-linear control methods. It is shown that
the suspension used fuzzy logic and neural network control methods has
less impact response and lower vibration intensity than differential
geometry theory control strategy, and has more superior performance.
Key words: Semi-active suspension Non-linear control MR damper
Differential geometry Fuzzy logic Neural network
CLC No: U463
国家自然科学基金(51035030)和重庆大学骨干教师基金(2002325)资助项目.
Received 20040709, received in revised form 20041221
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