A Hybrid Tracking Control Strategy for an Unmanned Underwater Vehicle Aided with Bioinspired Neural Dynamics

TL;DR

This paper introduces a hybrid control approach for unmanned underwater vehicles that combines bioinspired neural dynamics with advanced control techniques to achieve smooth, continuous, and reliable navigation in complex underwater environments.

Contribution

It proposes a novel hybrid control strategy integrating bioinspired neural dynamics with enhanced backstepping and sliding mode controls for UUVs.

Findings

Ensures smooth velocity and torque commands in UUV control.

Reduces chattering in control signals compared to traditional methods.

Improves control signal smoothness in complex underwater environments.

Abstract

Tracking control has been a vital research topic in robotics. This paper presents a novel hybrid control strategy for an unmanned underwater vehicle (UUV) based on a bioinspired neural dynamics model. An enhanced backstepping kinematic control strategy is first developed to avoid sharp velocity jumps and provides smooth velocity commands relative to conventional methods. Then, a novel sliding mode control is proposed, which is capable of providing smooth and continuous torque commands free from chattering. In comparative studies, the proposed combined hybrid control strategy has ensured control signals smoothness, which is critical in real world applications, especially for an unmanned underwater vehicle that needs to operate in complex underwater environments.