Optimal estimation and control of non-stationary response of a two-degree-of-freedom vehicle model

Abstract The active control of the non-stationary response of a 2-DOF vehicle model is studied. Stochastic optimal estimation and control theories have been used to estimate the states and to derive the control laws, respectively. Control laws involving complete and perfect state measurements and limited state measurements with additive noise are considered. In the case of limited state measurements, a Kalman filter has been used to estimate the unknown states. The performances of various active systems are compared with that of a corresponding passive system (zero control force) with respect to ride comfort, suspension working space, roadholding and control effort. It is shown that in some cases one can obtain almost as good as performance with limited state feedback control as with a full state feedback active system.

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