Predefined-Time Cooperative Formation Control of Multiple Underactuated Unmanned Surface Vessels With Smooth Switching Topology

Abstract

In this paper, a predefined-time adaptive fuzzy neural network (PTFNN) fault-tolerant controller is proposed for multiple underactuated unmanned surface vessels (USVs) subject to both actuator faults and input saturation. First, a distributed predefined-time state observer (DPTSO) is designed to estimate the states of the virtual leader, and the unknown nonlinear function consisting of modeling uncertainty, external environmental disturbances, and actuator faults is approximated by PTFNNs. Second, a smooth switching topology algorithm is proposed to solve the problem of changing communication relationships among USVs during the process of changing formation. Third, on the basis of a predefined-time auxiliary dynamic system, a saturation function is constructed to further constrain the control input, smooth the change in the control input, and solve the problem of a nonzero initial control signal. Finally, the stability analysis proves that all the signals within the closed-loop system can converge within a predefined time. Numerical simulations and comparisons with existing methods demonstrate the effectiveness and superiority of the proposed algorithm.