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Wen Pang et al.
Summary: This paper investigates the control of multiple underactuated autonomous underwater vehicles (AUVs) to achieve desired formation shapes. The authors propose a method based on distance-based graph rigidity and affine transformation (GR-AT) algorithm. The GR-AT algorithm utilizes backstepping technology and affine transformation properties to solve the formation control problem and transform the nominal formation into the desired formation shape. The Lyapunov stability theory is used to ensure the boundedness of distance errors.
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IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS
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Linling Wang et al.
Summary: This paper presents a fixed-time event-triggered obstacle avoidance consensus control method for a multi-AUV time-varying formation system in a 3D environment, using an improved artificial potential field and leader-follower strategy (IAPF-LF). The proposed fixed-time control achieves the desired formation within a fixed settling time in any initial system state. An event-triggered communication strategy is developed to govern the communication among AUVs, reducing communication energy consumption. The time-varying formation obstacle avoidance control algorithm based on IAPF-LF avoids static and dynamic obstacles, maintains the desired formation in the presence of external disturbances, and ensures no Zeno behavior under the fixed-time event-triggered consensus control strategy.
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Yunbiao Jiang et al.
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Cheng Zhu et al.
Summary: This paper investigates the tracking control problem for the marine surface vessel (MSV) under external disturbances, parametric uncertainties, actuator faults, and saturation constraints. A new appointed-time performance function is designed, and a modified backstepping control design process is conducted to achieve the approximation-free prescribed performance control with appointed-time convergence. The developed control scheme possesses features of quantitatively characterizing performance, high robustness against disturbances and uncertainties, fault-tolerant and anti-saturation capabilities.
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Mingcong Li et al.
Summary: This study investigates the containment problem of networked underactuated unmanned surface vehicles (USVs) guided by multiple virtual leaders using an event-triggering control mechanism. The study introduces a finite-time observer, a guidance law, and an event-triggered-based control law to tackle the problem. Stability analysis shows that the closed-loop system is finite-time stable.
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Jawhar Ghommam et al.
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Yuxin Zheng et al.
Summary: This article focuses on the distributed event-triggered affine formation control problem for multiple under-actuated marine surface vehicles (UMSVs) considering affine transformation and communication energy consumption under a directed interaction topology. Firstly, the affine transformation mechanism is adopted to improve the flexibility and maneuverability of the formation. Then, an event-triggered mechanism is proposed to reduce communication frequency between vehicles and save computation resources while excluding the Zeno behavior. Numerical simulations demonstrate the effectiveness of the proposed formation controller.
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Jun Ning et al.
Summary: This paper addresses the distributed formation control problem for multiple under-actuated unmanned surface vehicles (USVs) in the presence of input quantization, external disturbances, and model uncertainties. A two-level distributed guidance and neuro-adaptive quantized control architecture is proposed to achieve a time-varying formation. Simulation results demonstrate the effectiveness of the proposed method.
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Frederic Mazenc et al.
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EUROPEAN JOURNAL OF CONTROL
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Jianfei Lin et al.
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Xin Hu et al.
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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
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Yu Lu et al.
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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
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Qi Zhou et al.
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IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
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Guoqing Xia et al.
Summary: This paper presents a dual closed-loop fast integral terminal sliding mode control method for a multi-underactuated AUV formation system, which addresses uncertainties and disturbances by incorporating an adaptive neural network controller and a virtual leader. The proposed technique effectively overcomes the traditional method's problem of formation tracking errors not converging to zero, improving stability and robustness of the system.
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