Robust Depth and Heading Control System for a Novel Robotic Dolphin With Multiple Control Surfaces

For field tasks, it is quite challenged to operate in a complex environment for the underwater robots, especially for those with multiple control surfaces due to different response and gain characteristics. To this end, this paper develops a highly integrated robotic dolphin followed by a robust motion control system. For better maneuverability and fault-tolerant capabilities, a newly-designed robotic dolphin is presented, owning a wide array of sensors and multiple control surfaces, in which passive flukes are particularly applied. On this basis, a robust motion control system is proposed, including a depth controller based on velocity-related allocation strategies and a heading controller based on clearance compensation. In detail, considering the degradation of motion performance caused by passive flukes, a sliding mode controller for gain uncertainty and an allocation-related parameter tuning strategy for inputs response characteristics are designed. Extensive simulations and aquatic experiments are conducted, and the obtained results demonstrate the satisfied maneuverability of the designed prototype and the effectiveness of the proposed methods. This study can lay a foundation for further development of robotic dolphins with a robust motion system to execute complex tasks in the field. Note to Practitioners—This paper is inspired by the issue of robust motion control system for a newly-designed practical robotic dolphin that possesses a passive tail and redundant control surfaces. The traditional methods are usually susceptible to uncertainties in the passive tail gain, exhibiting degraded control performance. Moreover, control oscillations and slow convergence speed often occur caused by neglecting the characteristics of different control surfaces, including response patterns and clearance. This paper suggests a robust depth controller based on velocity-related allocation strategies and a robust heading controller based on clearance compensation. Specifically, an allocation-related parameter tuning strategy is given by considering inputs response characteristics, including response speed, saturations, and hydrodynamic force variation patterns. To guarantee fine regulations of heading control, a nonlinear disturbance observer (NDOB)-based clearance compensation is proposed. Extensive aquatic experiments on the newly-designed robotic dolphin verified the effectiveness of the proposed methods. It is envisioned that all these presented results can provide valuable engineering practice insights for industry practitioners.

I. Introduction

Natural evolution has led to the emergence of numerous fish and cetacean with high aquatic propulsion capability. By imitating the morphological structure, swimming mechanism, and behavioral patterns, researchers have developed a series of biomimetic underwater robots [1], [2], [3], [4], [5], [6], [7], which feature high maneuverability, strong adaptability, enhanced stealth, and low disturbance. Specifically, due to the excellent pitching maneuverability and efficient gliding/stroking behavior of dolphins [8], [9], [10], there has been a strong interest in the development of a high-performance biomimetic robotic dolphin. Li et al. [11] proposed a robotic fish that integrated the dorsoventral swimming and the shark-like lateral oscillation, enabling omnidirectional thrust generation. Wu et al. [12] designed a robotic dolphin that combined both gliding and flapping motion to improve the efficiency and agility. Yu et al. [13] developed a leaping robotic dolphin with outstanding pitching maneuverability and fast swimming capabilities. However, existing robotic dolphin platforms have predominantly focused on the exploration of dolphin-like propulsion performance, often lacking robust environmental perception capabilities and redundant driving mechanisms, which results in limited environmental adaptability, confined autonomy, as well as the absence of the ability to perform tasks in field environments.