A Torque Control Strategy for a Robotic Dolphin Platform Based on Angle of Attack Feedback.

Area of Science:

• Robotics
• Biomimetics
• Fluid Dynamics

Background:

• Biological fish optimize swimming efficiency by sensing water flow and adjusting caudal fin angle of attack (AoA).
• This biological mechanism involves tail muscle control, altering tail stiffness for optimal propulsion.
• Maintaining an optimal AoA is crucial for efficient movement and enhanced propulsion in aquatic environments.

Purpose of the Study:

• To propose a tail joint motion control scheme based on AoA feedback for high-speed swimming in bionic dolphins.
• To address limitations in tail and waist joint motor coordination during high-frequency movements.
• To improve the overall motion performance and propulsive efficiency of a robotic dolphin.

Main Methods:

• Analysis of the kinematic characteristics and hardware of a designed robot dolphin.
• Development of a compensation model for friction and latex skin-restoring forces.
• Implementation of a fuzzy inference-based joint angle control algorithm for tail joint torque mode control.
• Design of a closed-loop tail joint control scheme utilizing AoA feedback.

Main Results:

• The proposed fuzzy inference algorithm effectively tracks desired joint angles in torque mode.
• The AoA feedback control scheme demonstrably improves the motion performance of the bionic dolphin.
• Experimental validation confirms the effectiveness of the developed motion control strategy.

Conclusions:

• The AoA feedback control scheme is effective for enhancing the high-speed swimming capabilities of bionic dolphins.
• The study successfully addresses challenges in coordinating robotic fish joints for improved efficiency.
• This research contributes to advancements in biomimetic robotics and underwater propulsion systems.