This paper investigates the finite‐time consensus tracking problem for second‐order nonlinear multi‐agent systems subject to the actuator bias fault. Based on the sliding mode control and prescribed performance control, two distributed fault‐tolerant consensus protocols are proposed for the sudden bias fault and the slowly varying bias fault of the actuator. The first protocol adopts a passive fault‐tolerant control scheme based on the robustness of the system, which has a simple structure, and is timely and effective against sudden faults. In the second protocol, a novel nonlinear recursive sliding mode surface is designed, and a distributed fault observer is proposed to compensate the influences caused by actuator faults actively. Both of the protocols can prescribe the transient and steady‐state performance of the system. Finally, the performances of the two protocols are verified by two simulation cases for the attitude systems of multiple unmanned underwater vehicles.

This article investigates the three-dimensional trajectory tracking control problem for an underactuated autonomous underwater vehicle in the presence of parameter perturbations and external disturbances. An adaptive robust controller is proposed based on the velocity control strategy and adaptive integral sliding mode control algorithm. First, the desired velocities are developed using coordinate transformation and the backstepping method, which is the necessary velocities for autonomous underwater vehicle to track the time-varying desired trajectory. The bioinspired neurodynamics is used to smooth the desired velocities, which effectively avoids the jump problem of the velocity and simplifies the derivative calculation. Then, the dynamic control laws are designed based on the adaptive integral sliding mode control to drive the underactuated autonomous underwater vehicle to sail at the desired velocities. At the same time, the auxiliary control laws and the adaptive laws are introduced to eliminate the influence of parameter perturbations and external disturbances, respectively. The stability of the control system is guaranteed by the Lyapunov theorem, which shows that the system is asymptotically stable and all tracking errors are asymptotically convergent. At the end, numerical simulations are carried out to demonstrate the effectiveness and robustness of the proposed controller.

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