Adaptive output feedback super twisting algorithm for trajectory tracking control of USVs with saturated constraints

This article investigates the trajectory tracking control of fully actuated unmanned surface vehicles (USVs) in the presence of lumped system uncertainty and input saturation. To address this problem, an output feedback scheme, which combines the saturated adaptive super twisting algorithm and non-singular fast terminal sliding mode (SASTA-NFTSM) technique, is proposed. First, the velocities and lumped system uncertainty including external disturbances and model uncertainties, are estimated by a finite-time extended state observer (FTESO), simultaneously in finite time. Second, to deal with the saturation constraints on actuators, a novel sliding mode reaching law scheme, namely SASTA, that consists of an anti-windup compensator and a super twisting algorithm based on switching logic adaptive gains is proposed. Finally, the trajectory tracking control of USVs is solved with the non-trivial combination of SASTA and NFTSM. The chattering phenomenon can be effectively attenuated by virtue of the continuous control laws compared with the traditional NFTSM control (NFTSMC) approaches. The tracking errors are guaranteed to converge to zero in finite time. Comparative simulation results demonstrate the effectiveness and advantage of the proposed scheme.