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A good suspension system is of paramount importance to the operating performance of a vehicle and, consequently, to the safety and driving comfort of the passengers. Nevertheless, suspension systems are commonly susceptible to nonlinearity, parameter uncertainty, and exogenous perturbation, which can easily impair their effectiveness. This study first employs a full state feedback super twisting control (FS-STC) to stabilize both vertical displacement and pitch angle of a half-car suspension system in the presence of disturbances. FS-STC inherits the robust property of sliding mode control (SMC) while effectively attenuating the chattering phenomenon as one of its attractive features. However, FS-STC strictly requires both direct displacement and velocity state feedback, which implies additional sensors have to be installed, thus increasing the complexity of the physical structure and being prone to measurement noises. Therefore, a higher order sliding mode observer (HOSMO) based STC (HOSMO-STC) and an unscented Kalman filter (UKF) based STC (UKF-STC) are subsequently proposed to tackle this state availability problem. HOSMO estimates velocity states, thus reducing the dependence on state feedback for STC design. Meanwhile, UKF implementation takes further actions by utilizing more common and easily accessible relative displacements such as suspension strokes to estimate all concerned system states. Comparative simulation results demonstrate that UKF-STC offers better performance in terms of both convergence accuracy and chattering alleviation compared to FS-STC and HOSMO-STC while requiring the least information of state feedback.