This work provides a theoretical solution for increasing the resiliency of cyber-physical systems to cyber attacks and malfunctions. We propose a supervisory device that exists between the controller and actuator in a feedback loop that monitors and regulates control signals that would cause the system to reach an undesired state. We explore three approaches for calculating actuator limits: analytical, reachable set, and Monte Carlo simulations. Each method is applied to the Nomoto model for ship motion and a unmanned underwater vehicle inspired model. For each model, we examine each method's potential to maximize system maneuverability under safety constraints.