A six degrees of freedom half body vehicle suspension system is presented in the paper .The Back Propagation neural network algorithm and the Radial-Basis Function network algorithm is adopted to control the suspension system. With the aid of software Matlab/Simulink , the simulation model is obtained. A great deal of simulation work is done. Simulation results demonstrate that both the designed radius basis function neural network and the back propagation neural network work well for the proposed vehicle suspension model in the paper .
In this paper, a six degree of freedom half body vehicle suspension system is developed and the road roughness intensity is modeled as a filtered white noise stochastic process. Based on control theory, the fuzzy control system of the active suspension is established. With the aid of software Matlab/simulink, simulation process is done. Simulation results indicate that the proposed active suspension system proves to be effective in the vibration isolation of the suspension system. A mechanical dynamic model of the two degree of freedom quarter body of vehicle suspension system is
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 results demonstrate that the proposed active suspension system proves to be effective in vibration reduction and drive stability enhancement of the suspension system.
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