Abstract
The paper shows the steps for the preliminary studies of an AUV for shallow water: the first part illustrates the vehicle architecture and the philosophy that permeates the various design choices. In the second part illustrates an innovative method for increasing longitudinal stability based on Takagi-Sugeno (T-S) Fuzzy Inference System: it saves a lot of computational time and, by simplifying the calculation, it is also suitable for remarkably simple computers such as Arduino. in the third part is simulated the behavior of the AUV: thanks to the data taken from the previous hydrodynamic simulation, we can establish the behavior of its longitudinal stability and the computational savings due to the T-S method.
Highlights
IntroductionMethod Based on Takagi-SugenoThe purpose of the paper is to study a drone capable of autonomous exploration of the sea
Based on Takagi-SugenoThe purpose of the paper is to study a drone capable of autonomous exploration of the sea
The vehicle differs from the others because from the environmental point of view it is designed for shallow waters: areas that are exceedingly difficult to reach with ordinary autonomous underwater vehicles (AUVs)
Summary
Method Based on Takagi-SugenoThe purpose of the paper is to study a drone capable of autonomous exploration of the sea. It is imagined and so designed to perform many activities currently neglected because expensive to execute with traditional systems as, e.g., marine traffic control missions, monitoring of sandy/rocky coast, search and tracking of schools of fish, control of oil pipelines and submarine cables. For these missions it is necessary to have small vehicles but with extremely powerful engines, of compact architecture: most of the existing drones only partially satisfy any of these requirements. The study went through several phases: outline and detailed drawing, design of the control and attitude system. Since the classic algorithms are very time consuming, one of the main innovative objectives of this part of the work is to find “light” or simplified algorithms that allow the use of simple, reprogrammable and inexpensive systems such as Arduino thought the application of fuzzy logic to the attitude control system [1]
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