This article investigates a robust cooperative path following control algorithm for an unmanned surface vessel and unmanned aerial vehicles (USV-UAVs) that releases the design complexity and command transmission requirements for the potential significance to implement a maritime square search mission. The latter is a classical search pattern suggested by the international aeronautical and maritime search and rescue (IAMSAR) manual. To program the reference signals for the USV-UAVs simultaneously, the reference routes are programmed that uses a virtual ship and a virtual aerial. Therein, the information of the virtual aerials can be mapped from a virtual ship. Further, the desired attitude angles are derived under the cooperative virtual guidance framework. For a control part, a novel threshold rule of the dynamic event-triggered mechanism is reconstructed according to output errors to avoid the artificial parameter tuning and reduce the data transmission load from the controllers to the actuators. Besides, a L-function is designed to eliminate an effect caused by the model nonlinearities and disturbances. This ensures a lower design complexity of the control system. The stability of the proposed control algorithm is proved via the Lyapunov theorem. Finally, the effectiveness and the reasonable are evaluated on the simulation platform.

Cooperative Path Following Control of USV-UAVs Considering Low Design Complexity and Command Transmission Requirements

This article investigates the distributed event‐triggered affine formation maneuver control problem for multiple underactuated surface vessel (USV) systems with positive minimum inter‐event times (MIET). Unlike common formation control methods that only ensure the formation system to keep a fixed geometric shape, the proposed scheme enables multiple USVs maneuver as a group in translation, shearing, rotation, or combinations of them. The proposed control strategy is composed of two parts. First, a distributed event‐triggered observer (DETO) is proposed to observe the time‐varying target formation under the lack of global leaders' information and govern the inter‐vessel communications among the formation group. Besides, the MIET of the designed communication strategy is proved to be strictly positive and computable from formation configurations and control parameters. With these guarantees, the maximum communication frequency can be known in advance. Then, upon the DETO signals, the adaptive local tracking controller is subsequently synthesized for each vessel to realize the target formation track. Rigorous theoretical analysis and simulation results are finally conducted to verify the validness and effectiveness of the proposed algorithm.

Distributed observer based event‐triggered affine formation maneuver control for underactuated surface vessels with positive minimum inter‐event times

In this paper, a distributed bearing-based formation control scheme with finite-time convergency is proposed for multiple underactuated surface vessels (USVs). By virtue of the guide point-based model transformation method, the dimension of underactuated tracking error dynamics can be reduced from three to two. This allows us to convert the actuator model to a fully form that matches dimension-reduced tracking error dynamics. Further, to reduce the computation complexity, a finite-time recruited filter is designed according to first-order Levant differentiator. At meanwhile, auxiliary error compensation signals are introduced to address unknowns stemming from filter process and system dynamics. Since merely relative-distances and inner bearings are utilized in the proposed bearing-based formation approaches, the proposed control scheme provides a feasible solution to achieve formation control under body-fixed frame. Finally, theoretical analysis and numerical simulations are presented to demonstrate the efficacy. 

Distributed finite-time bearing-based formation control for underactuated surface vessels with Levant differentiator.

Deepwater oil and gas equipment is a complex and dynamic system that requires thorough risk assessment during its operation. Existing methods such as fault tree analysis, failure mode analysis, bow-tie analysis, and Markov models have been used to investigate risks related to deepwater equipment installation, fatigue, leaks, and blowouts. However, these approaches often overlook the impact of dynamic changes in oil well operations on the risk factors associated with deepwater equipment accidents. Therefore, there is a need for a comprehensive method that can assess the real-time dynamic safety of deepwater equipment under various failure modes. To address this gap, this work proposes a novel risk assessment method for deepwater equipment that incorporates preventive maintenance strategies and dynamic operating conditions. A dynamic Bayesian networks (DBNs) structure is established for the failure model of deepwater equipment. The fault modes of the subsystems and the dynamic and multi-state characteristics of the faults are considered, and the dynamic fault probabilities are calculated. The degree of failure consequences and the characteristic values of different failure modes are evaluated using the matter element theory. To validate the effectiveness of the proposed method, a study is conducted on the operation process of a subsea blowout preventer. The results demonstrate that dynamic risk assessment for deepwater equipment can be accurately and effectively performed using this method. In conclusion, a risk assessment framework is introduced in the research, which accounts for the preventive maintenance strategy and dynamic operating conditions of deepwater equipment. By combining DBNs and the matter element theory, a comprehensive approach is provided to evaluate the dynamic safety of deepwater equipment under different failure modes. The study on subsea blowout preventers serves as a practical demonstration of the efficacy of the proposed method. 

Dynamic risk assessment methodology of operation process for deepwater oil and gas equipment

Dynamic event-triggered trajectory tracking control for underactuated marine surface vessels with positive minimum inter-event time guarantees

This article studies the two‐layer leader‐follower optimal affine formation maneuver (AFM) control problem for multiple unmanned surface vessels (USV). The basic idea of the developed two‐layer control framework is to realize the time‐varying formation for the leader group in advance, and then let the follower USVs agilely respond to the target formation affinely localized by leaders. To realize this goal, a time‐varying formation reference system is first synthesized to describe leaders' target formation in the affine map of the nominal configuration. The reference system is set up by virtual vessel velocity command and unrotated geometric command, which make it possesses an intuitive application structure for operators to plan AFM commands in real‐time sensed surrounding environments. Then, by means of optimized backstepping design and the adaptive dynamic programming technique, actor‐only reinforcement learning controllers are established for USVs in both two layers to realize the optimal target formation tracking objective. For the proposed optimal controllers, the persistent excitation condition that is required by common optimal control schemes is also removed, which endows the presented scheme with lower computational complexity. Finally, theoretical analysis and simulation results illustrate the closed‐loop stability and the effectiveness of the presented scheme.

Two‐layer leader‐follower optimal affine formation maneuver control for networked unmanned surface vessels with input saturations

Trajectory tracking control for autonomous underwater vehicles under quantized state feedback and ocean disturbances

Distributed dynamic edge-based event-triggered formation control for multiple underactuated unmanned surface vessels

Piecewise deterministic Markov process for condition-based imperfect maintenance models

Event-Triggered Model-Parameter-Free Trajectory Tracking Control Autonomous Underwater Vehicles with Positive Minimum Inter-Event Time Guarantees

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