Abstract
This study presents a new intelligent control method, human-simulated intelligent control(HSIC) based on the sensory motor intelligent schema (SMIS), for a magneto-rheological(MR) suspension system considering the time delay uncertainty of MR dampers. Afterformulating the full car dynamic model featuring four MR dampers, the HSIC based oneight SMIS is derived. A neural network model is proposed to compensate for the uncertaintime delay of the MR dampers. The HSIC based on SMIS is then experimentally realizedfor the manufactured full vehicle MR suspension system on the basis of the dSPACEplatform. Its performance is evaluated and compared under various road conditions andpresented in both time and frequency domains. The results show that significantgains are made in the improvement of vehicle performance. Results include areduction of over 35% in the acceleration peak-to-peak value of a sprung mass over abumpy road and a reduction of over 24% in the root-mean-square (RMS) sprungmass acceleration over a random road as compared to passive suspension withtypical original equipment (OE) shock absorbers. In addition, the semi-active fullvehicle system via HSIC based on SMIS provides better isolation than that via theoriginal HSIC, which can avoid the effect of the time delay uncertainty of the MRdampers.
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