Barrier Lyapunov Function-based adaptive prescribed-time extended state observers design for unmanned surface vehicles subject to unknown disturbances

• Published in: Ocean engineering Vol. 270; p. 113671
• Main Authors: Zhao, Jie, Cai, Chengtao, Liu, Yongchao
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15.02.2023
• Subjects: Adaptive mechanism; Barrier Lyapunov function; Extended state observers; Prescribed performance function; Prescribed-time; Unmanned surface vehicles; Barrier Lyapunov function; Adaptive mechanism; Prescribed-time; Prescribed performance function; Unmanned surface vehicles; Extended state observers
• ISSN: 0029-8018; 1873-5258
• DOI: 10.1016/j.oceaneng.2023.113671

This paper studies the prescribed-time observer design problem for unmanned surface vessels (USVs) in the presence of unknown ocean disturbances. An adaptive prescribed-time extended state observer (APESO) is designed to estimate the lumped disturbances consisting of model uncertainties and external disturbances due to wind, waves and ocean currents and reconstruct unmeasured velocities information for USVs. Different from existing finite/fixed-time extended state observers for USVs, the APESO can accomplish observations within a prescribed time with a tiny peaking observation errors. The upper bound of the settling time of the APESO is tightly and explicitly prescribed by only one design parameter, resulting in a simple and weakly conservative parameter tuning process for temporal demands. Moreover, the barrier Lyapunov function (BLF) and prescribed performance function (PPF)-based adaptive mechanism is introduced into the observer design, which can improve the transient performance by self-adjusting the observer correction term along with the ocean disturbance amplitude. Finally, the performance and ascendancy of the proposed APESO are exhibited by simulation comparisons. •An APESO is designed to accurately estimate the lumped disturbance and reconstruct velocities information of USVs within a prescribed time. The upper bound of the settling time of APESO is tightly prescribed by only one design parameter regardless of initial conditions.•In practice, the widespread input saturation of USVs would then introduce conditions on the initial states, which is a not limit condition for prescribed-time approach than existing finite-time approach.•For time-critical tasks such as trajectory tracking, dynamic position and target tracking, the APESO makes the tuning procedure more straightforward than finite-time ESOs and fixed-time ESOs.•By introducing an adaptive mechanism based on BLF and PPF techniques, the transient performance of APESO can be significantly improved through self-adjusting the observer’s correction term along with ocean disturbance amplitude, which outperforms non-adaptive observers.•The feasibility of APESO combined with the predefined-time sliding mode control algorithm has been discussed. This paper provides a novel prescribed-time control scheme based on APESO for USVs without switching form.