Formation Control Of Autonomous Underwater Vehicles Research Articles

Distributed predictive formation control for autonomous underwater vehicles under dynamic switching topology

Numerous existing autonomous underwater vehicles (AUVs) formation control works have focused on the preconfigured communication topology. However, the complex marine environment reveals the limitations and unreliability of the fix topology scheme. In this paper, the formation control of AUVs is investigated under dynamic switching topology. In order to realize this objective, the 2-D Delaunay triangulation and Jaccard index are introduced. A formation control system based on intermittent broadcast, rather than the traditional distributed control system, is established based on a leader-follower strategy. During the process of formation moving, the input constraints, vehicle collision avoidance and input saturation needed to be noted. To this end, the model predictive control algorithm is employed to design the formation controller, and the stability of the formation control system is proved by the average residence time notion and Lyapunov stability. The numerical simulations are exhibited to illustrate the effectiveness of the proposed formation control schemes in connectivity preservation and formation generation.

Finite-Time Formation Control for Autonomous Underwater Vehicles with Limited Speed and Communication Range

Cooperative control of multiple autonomous underwater vehicles (AUVs) plays an important role on marine scientific investigation and marine development. The formation of multi-AUV can significantly enhance applications on the marine sampling, imaging, surveillance and communications. Compared to the formation control of multi-robot, the formation control of multi-AUV is particularly difficult, especially on controlling attitude and direction of AUV; what is more, the communication method among AUVs is acoustic. When communication distance increases, the communication qualities deteriorate quickly; this mainly makes time-delay, signal attenuation and distortion. Although formation control of multiple AUVs obtains a wide range of attention in recent years, the fruits on formation control problem are less than ones on land multi-robot problems. For example, Fiorelli conducted a collaborative and adaptive sampling research of multi-AUV at the Monterey Bay [; Yu and Ura carried out the cable-based modular fast-moving and obstacle-avoidance experiments, and presented an interconnected multi-AUV system with three-dimension sensors. On the aspect of formation control framework [2-, [ proposed a four-layer cooperative control strategy based on hierarchical structure; [ proposed a hierarchical control framework based on hybrid model. In addition, Yang converted a nonholonomic system to a chain one and designed a controller to implement a leader-follower formation for multiple AUVs in [. The formation control for multiple autonomous underwater vehicles is rather different than the control methods for other vehicles, because the formation control for AUVs is of its characteristics, such as the large-scale distribution in space. The finite-time consensus controller designing based on finite-time control and consensus problem has important theoretical and practical significance. The decentralized controller methods for the autonomous underwater vehicle are applied more and more, but they ignore the coupling relationship between them. Another method is that an AUV is modeling as an agent, but this method ignores attitude characteristics of AUVs (pitch, roll and yaw). In this paper, we consider the cooperative control problem in three dimensional spaces. Finite-time formation for Autonomous Underwater Vehicles (AUVs) with constraints on communication range is investigated. We proposed a two-layer finite-time consensus control law, to avoid leading to collapse on formation because of failure leader, all AUVs are arrayed in the same level and each AUV can obtain global formation information. Finally, the simulation results show the effectiveness of the control strategy.