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In this paper, two main subjects are dealt with: stabilization of supercavitating vehicles in depth mode and estimating the state variables of the vehicle in order to control the vehicle in this mode. Using the feedback linearization method, the model of the system is linearized and a linear quadratic regulator is designed for the system to stabilize it. This method needs to feedback all states of the system, while measuring all the states is practically infeasible. Then, it is needed to estimate some of the states using the model of the system and the sensor measurements. This is performed here using two well-known filters of EKF and UKF. Through simulations, it is shown that both filters can estimate the states of the system in the depth mode, stabilize the vehicle in this mode and reject the disturbances. It is observed that each filter can estimate some of the states more accurately. In simulations, the performances of the designed controllers are examined, practical issues like actuator saturation are taken into account and the ability of the controllers to stabilize the vehicle is demonstrated.

Stabilization of a Supercavitating Vehicle in Depth Mode using Linear Quadratic Regulator Method and EKF and UKF Estimators