Fuzzy modeling and control for Autonomous Underwater Vehicle

Autonomous Underwater Vehicles (AUVs) have gained importance over the years as specialized tools for performing various underwater missions in military and civilian operations. The autonomous control of underwater vehicles poses serious challenges due to the AUVs' dynamics. AUVs dynamics are highly nonlinear and time varying and the hydrodynamic coefficients of vehicles are difficult to estimate accurately because of the variations of these coefficients with different navigation conditions and external disturbances. This work deals with the off-line system identification of the AUV dynamics to obtain the coupled six degree of freedom and nonlinear dynamic model without hydrodynamic parameter estimation to overcome the uncertain external disturbance and the difficulties of modeling the hydrodynamic forces of the AUVs based upon fuzzy techniques. Fuzzy control system is applied to guide and control the AUV using both fuzzy modeling and mathematical model. The simulation results show that the performance of the AUV with the fuzzy control with fuzzy model is having better dynamic performance as compared to the fuzzy control with mathematical model, even in the presence of noise and parameter variations.

I. Introduction

The autonomous underwater vehicle (AUV) is an underwater system that contains its own power and is controlled by an onboard computer. Many names are given to these vehicles according to their configuration such as remotely operated vehicles (ROVs), unmanned underwater vehicles (UUVs), and submersible devices. The fundamental task for these devices is fairly well defined as the vehicle is able to follow a predefined trajectory to reach the final destination. AUVs offer many advantages for performing difficult tasks submerged in water. The main advantage of the AUV is that it does not need a human operator. Therefore, it is less expensive than a human operated vehicle and is capable of doing operations that are too dangerous for humans. It operates in conditions and perform task that humans are not able to do efficiently or at all (Smallwood, 2004).