Overshoot Reduction Using Adaptive Neuro-Fuzzy Inference System for an Autonomous Underwater Vehicle

In this paper, an adaptive depth and heading control of autonomous underwater vehicle using the concept neuro-fuzzy inference system (ANFIS) is designed. The dynamics have six degrees freedom, which are highly nonlinear time-varying. It affected by environmental effects such as ocean currents tidal waves. Due to designing, a stable controller in difficult end achieve. Fuzzy logic neural network blocks make up proposed design angle vehicle. trained back-propagation algorithm. presence noise parameter variation, controller’s performance compared with that self-tuning fuzzy-PID fuzzy controller. Simulations conducted obtain both models terms overshoot, rise time result exhibit superior can eliminate effect uncertainty.