On-Line Adaptive Fuzzy Modeling and Control for Autonomous Underwater Vehicle

Abstract

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 AUV poses serious challenges due to the AUVs’ dynamics. Its 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 is going to deal with the system identification of AUV dynamics to obtain the coupled nonlinear dynamic model of AUV as a black box. This black box has an input-output relationship based upon on-line adaptive fuzzy technique to overcome the uncertain external disturbance and the difficulties of modeling the hydrodynamic forces of the AUVs instead of using the mathematical model with hydrodynamic parameters estimation. The fuzzy model’s parameters are adapted using the back propagation algorithm. Fuzzy control system is applied to guide and control the AUV with mathematical model, fuzzy model and adaptive fuzzy model. The simulation results show that the performance of the AUV with the fuzzy control with adaptive fuzzy model is having better dynamic performance as compared to others model even in the presence of noise and parameter variations.

Based on “Fuzzy Modeling and Control for Autonomous Underwater Vehicle”, by “O. Hassanein, Sreenatha G. Anavatti and Tapabrata Ray” which appeared in the Proceedings of the 5th International Conference on Automation, Robotics and Applications (ICARA 2011). © 2011 IEEE.