A hybrid tracking control strategy for an unmanned underwater vehicle aided with bioinspired neural dynamics. Issue 3 (9th September 2022)

• Record Type: Journal Article
• Authors: Xu, Zhe; Yan, Tao; Yang, Simon X.; Gadsden, S. Andrew
• Is Part Of: IET cyber-systems and robotics. Volume 4:Issue 3(2022)
• Page Start: 153
• Page End: 162
• Publication Date: 2022-09-09
• Subjects: backstepping -- bioinspired neural dynamics -- sliding mode control -- unmanned underwater vehicle; Robotics -- Periodicals; Cybernetics -- Periodicals; Cybernetics; Robotics; Periodicals; 629
• DOI: 10.1049/csy2.12060
• Languages: English
• ISSNs: 2631-6315

Abstract

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 signal smoothness, which is critical in real‐world applications, especially for a UUV that needs to operate in complex underwater environments.