Application of IPSO-BP Network Algorithm in Semi-active Suspension Control

To improve the performance of semi-active suspension,the paper proposes an IPSO-BP algorithm as an adaptive semi-active suspension control algorithm.The IPSO algorithm improves the standard PSO algorithm to perfect the convergence rate and the capability of global convergence and is used for the BP neural network learning algorithm for adaptive semi-active suspension control.Adaptive controller has a two-unit structure neural network.One is an input controller,which adjusts the value of semi-active suspension damping in accordance with the road input;and the other is a semi-active suspension identifier which is used for online identification.Through the adaptive control test of the semi-active suspension based on the semi-active suspension controller,results show that the controller based on the IPSO-BP algorithm obviously improves the comfort and ride quality of the car.The vertical acceleration of the car body reduces 21.73% compared with the PSO-BP semi-active suspension.This algorithm improves the vehicle suspension performance.