NEURO-FUZZY ADAPTIVE CONTROL AND MODELING A THRUSTER OF AUTONOMOUS NDERWATER VEHICLES

Abstract

The paper presents a direct adaptive fuzzy approach for parameter identification and control of unknown nonlinear systems. To prove the performance of the proposed method an autonomous underwater vehicle (AUV) is modeled using an Adaptive Neuro-Fuzzy Inference System (ANFIS). To guaranty high accuracy the model is adapted online using system input and output data. From the model the current process parameters are identified and utilized for controller design. Here, Single Step Ahead Direct Adaptive Control and Multi Steps Ahead Direct Control schemes are considered.