Distributed prescribed performance containment control for unmanned surface vehicles based on disturbance observer.

This paper introduces a distributed containment control strategy for multiple unmanned surface vehicles (USVs) under the unknown external disturbances. The communication network of the USVs is a fixed, directed topology and only a part of the follower USVs can read the states of leader USVs. To guarantee the transient and steady-state performance of the system, the tracking errors are converted into new error functions. By utilizing the disturbance observer, the external disturbances are effectively estimated. According to the new group of errors, a distributed containment controller is proposed with the estimated external disturbances. Furthermore, using graph theory and Lyapunov approach, it is proved that all variables of the multiple USV systems are bounded and the tracking errors can be confined within the specified performance ranges. Finally, simulation results illustrate the effectiveness of the designed distributed containment controller.

Modeling and sliding mode-based attitude tracking control of a quadrotor UAV with time-varying mass.

In the practical applications, the mass of a quadrotor unmanned aerial vehicle (UAV) would be time-varying. This time-varying mass will deteriorate the control performance of UAV. To solve this challenge, the mathematical modeling problem of a quadrotor UAV with time-varying mass is first investigated in this paper. The nonlinear dynamics describing the six-degrees-of-freedom full motion is established. Based on the established model, taking attitude tracking control problem into consideration, a robust control scheme is then designed via the sliding mode control theory. Applying the developed proposed approach, the desired trajectory is followed with the attitude tracking error asymptotically stabilized. The proposed controller has the capability of rejecting the external disturbance and the uncertainties induced by the time-varying mass. The feasibility of the established model and the effectiveness of the presented control approach are validated through a simulation study.

Distributed Finite-Time Fault-Tolerant Containment Control for Multiple Unmanned Aerial Vehicles.

This paper investigates the distributed finite-time fault-tolerant containment control problem for multiple unmanned aerial vehicles (multi-UAVs) in the presence of actuator faults and input saturation. The distributed finite-time sliding-mode observer (SMO) is first developed to estimate the reference for each follower UAV. Then, based on the estimated knowledge, the distributed finite-time fault-tolerant controller is recursively designed to guide all follower UAVs into the convex hull spanned by the trajectories of leader UAVs with the help of a new set of error variables. Moreover, the unknown nonlinearities inherent in the multi-UAVs system, computational burden, and input saturation are simultaneously handled by utilizing neural network (NN), minimum parameter learning of NN (MPLNN), first-order sliding-mode differentiator (FOSMD) techniques, and a group of auxiliary systems. Furthermore, the graph theory and Lyapunov stability analysis methods are adopted to guarantee that all follower UAVs can converge to the convex hull spanned by the leader UAVs even in the event of actuator faults. Finally, extensive comparative simulations have been conducted to demonstrate the effectiveness of the proposed control scheme.

Trajectory exponential tracking control of unmanned surface ships with external disturbance and system uncertainties.

Any unmanned surface ship is subject to system uncertainty, unknown parameters, and external disturbance induced by the wind, the wave loads, and the ocean currents. They may deteriorate ship's control accuracy. This paper aims to solve the trajectory tracking control problem of unmanned surface ships with disturbance and system uncertainty accommodated simultaneously. An estimator-based backstepping controller is presented with an estimator designed to provide a precise estimation of the disturbance and uncertainties. The proposed controller ensures the closed-loop tracking system to be globally exponentially stable. The trajectory tracking error and the estimation error of disturbance and uncertainties are globally exponentially stable. The key feature of the developed control scheme is that it is more robust to disturbances and system uncertainties. Simulation results are further presented to validate the effectiveness of the approach.