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In field operation, the boom must be kept parallel to the ground or crop canopy, resulting in unwanted movement of the boom due to the unevenness of the soil surface. The most important vibrations, affecting the spray distribution pattern, are rolling (rotational motion around an axis along the driving direction) causing spray boom motions in the vertical plane. In order to reduce the unevenness in spray deposit, the majority of current agricultural sprayers are equipped with a vertical suspension system to attenuate roll of the boom. The suspension tries to keep the boom at right angles to gravity by isolating the boom from vibrations of the tractor or trailer. Aiming at the problem of low accuracy and poor stability caused by parameter uncertainties and random disturbances in the passive and active pendulum type suspension system, the adaptive robust control algorithm based on model compensation was developed. Firstly, the nonlinear dynamic model and geometric equation of the pendulum active and passive suspension were established by using the dynamic analytical modeling method. Then, based on the nonlinear model of the suspension system, the design of adaptive robust controller was carried out, which integrated many parameter uncertainties existing in the suspension system and the electrohydraulic position servo system model, and also took into account of uncertain nonlinear factors such as uncompensated friction and disturbance of the system. It was proved theoretically that the designed controller can guarantee the transient performance and steadystate accuracy of the output tracking control system when the model parameters were uncertain and nonlinear. In order to make the designed control algorithm easier to understand and apply, the active and passive suspension of 28m large boom driven by single rod hydraulic actuator was used as an example. The platform was tested and verified by the control algorithm, and the Stewart sixdegreeoffreedom motion platform was used to simulate the motion interference of the chassis. The proposed controller and feedback linearization controller, robust feedback controller, and PID controller were compared on the test bench. The maximum tracking error of the designed adaptive robust controller based on model compensation was 0.148°, while the feedback linearization controller was 0.201°, the robust feedback controller was 0.51°, and the PID controller was 0.48°, which verified that the design of the controller can ensure the asymptotic tracking performance and steadystate tracking accuracy of the control system by using a smaller feedback gain coefficient in the presence of parameter uncertainty and disturbance.