A Hybrid Tracking Control Strategy for an Unmanned Underwater Vehicle Aided with Bioinspired Neural Dynamics
This work addresses the need for smooth control signals in real-world UUV operations in complex underwater environments, representing an incremental improvement over conventional methods.
The paper tackled the problem of tracking control for unmanned underwater vehicles by developing a hybrid control strategy combining enhanced backstepping kinematic control and a novel sliding mode control, resulting in smooth velocity and torque commands that avoid sharp jumps and chattering.
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.