The autonomous surface vehicle (ASV) owned by the University of Rhode Island currently uses a PID controller that is insufficient for its maneuvering goals. The goal develop a robust linear controller based on state space models that is able to follow a given path with minimal error. A linear controller was developed that used inverse filters to follow a desired path with greater accuracy and used new methods for choosing feedback gains to provide greater H_∞ robustness. The controller was tested in simulation by performing an ellipse maneuver on a nonlinear dynamic positioning model of the CyberShip II under disturbances, measurement noise, and model perturbations. It was found that these new methods tracked the desired ellipse with lower error than existing pole placement methods and no inverse filter. These methods show promise for real world implementation on URI's ASV once resources become available for approximate modeling.