Preliminary Study for AUV: Longitudinal Stabilization Method Based on Takagi-Sugeno Fuzzy Inference System.

Area of Science:

• Robotics
• Control Systems
• Ocean Engineering

Background:

• Preliminary studies for Autonomous Underwater Vehicle (AUV) development are crucial for shallow water applications.
• Vehicle architecture and design choices significantly impact AUV performance.
• Longitudinal stability is a key factor in AUV maneuverability and mission success.

Purpose of the Study:

• To present the preliminary design and studies of an AUV tailored for shallow water environments.
• To introduce an innovative method for enhancing AUV longitudinal stability.
• To evaluate the computational efficiency of the proposed stability control method.

Main Methods:

• Detailed illustration of the AUV's vehicle architecture and underlying design philosophy.
• Implementation of a Takagi-Sugeno (T-S) Fuzzy Inference System to improve longitudinal stability.
• Hydrodynamic simulations to analyze AUV behavior and validate the T-S method's effectiveness.

Main Results:

• The proposed T-S Fuzzy Inference System significantly enhances longitudinal stability.
• The T-S method offers substantial computational time savings.
• The simplified calculations are compatible with simple computing platforms like Arduino.

Conclusions:

• The developed AUV design and stability control method are suitable for shallow water operations.
• The Takagi-Sugeno Fuzzy Inference System provides an efficient and computationally inexpensive solution for AUV stability.
• The study demonstrates the feasibility of implementing advanced control strategies on resource-constrained hardware.