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This paper discusses the design of a Model Predictive Controller for a vehicle active suspension system and presents the experimental results obtained in the evaluation of the controller performance. The Model Predictive Control methodology described here, utilizes the road profile ahead of the vehicle as preview information and also takes into explicit consideration the physical constraints on the suspension travel. The advantages in the use of preview information in active suspension control have been studied by several researchers. The explicit consideration of the physical limits on the suspension travel becomes an important factor under rough road conditions such as the ones encountered by off-road vehicles. A computationally efficient version of the predictive controller was developed so as to be implementable on-line. The experimental evaluation of the controller was performed on the UC Berkeley Active Suspension Test Rig.

This paper presents an output redefinition strategy for the design of a dual sliding surface force tracking controller for a two degrees of freedom electrohydraulic active suspension system. In the proposed approach, an appropriately redefined output is made to track a modified reference trajectory, which effectively compensates for undesired behavior and controller bandwidth limitations introduced into the system by the built-in feedback of the suspension velocity to the actuator dynamics. Results show a noticeable performance improvement in the controller’s ability to track a variety of desired force reference trajectories, while adequately handling external road disturbances. The careful design of this force tracking controller is an important step towards implementation and realization of the full potential of several linear active suspension control techniques that consider the suspension actuator force as the input to the system. The experimental evaluation of the controller was performed on the UC Berkeley Active Suspension Test Rig.