Optimization of depth control for Unmanned Underwater Vehicle using surrogate modeling technique

The underwater environment poses a difficult challenge for autonomous underwater navigation. A standard problem of underwater vehicles is to maintain its position at a certain depth in order for it to perform desired operations. An effective controller is required for this purpose and hence the design of a depth controller for an Unmanned Underwater Vehicle is described in this paper. The control algorithm is simulated by using the Marine Guidance Navigation and Control Simulator. The project is to show how a Radial Basis Function Surrogate Model can be used to tune the scaling factors of fuzzy logic controller quickly. By using offline optimization approach, Surrogate Modeling or sometimes called Metamodeling has been done to minimize the Integral Square Error between the set point and the measured depth of the Unmanned Underwater Vehicle.