Observer-based fixed-time dynamic surface tracking control for autonomous surface vehicles under actuator constraints and denial-of-service attacks Show others and affiliations
2024 (English) In: Applied Mathematics and Computation, ISSN 0096-3003, E-ISSN 1873-5649, Vol. 465, article id 128403Article in journal (Refereed) Published
Abstract [en]
This paper proposes a novel trajectory tracking control strategy for autonomous surface vehicles (ASVs), subject to actuator constraints and under denial-of-service (DoS) attacks. Firstly, a fixed-time disturbance observer (FTDO) is used to estimate and compensate unknown external disturbances, which enhances the robustness of the motion system. Secondly, a novel fixed-time filter is designed by combining dynamic surface technology with fixed-time control, which avoids the problem of differential explosion, and reduces the filtering error. Lastly, in order to address the effects of actuator constraints and DoS attacks, an auxiliary system (AS) and a compensation system (CS) are included in the fixed-time dynamic surface controller based on FTDO. The proposed method improves the robustness, stability and accuracy of the closed-loop system. Additionally, the reference tracking error converges to the neighborhood of the origin within a fixed-time. The superiority of the proposed control method over traditional control strategies from the existing literature is demonstrated in simulations.
Place, publisher, year, edition, pages Elsevier, 2024. Vol. 465, article id 128403
Keywords [en]
Actuator constraints, Autonomous surface vehicles (ASVs), Dynamic surface control, Denial-of-service (DoS) attacks, Fixed-time disturbance observer, Fixed-time trajectory tracking control
National Category
Control Engineering
Research subject Automatic Control
Identifiers URN: urn:nbn:se:ltu:diva-101842 DOI: 10.1016/j.amc.2023.128403 ISI: 001102228500001 Scopus ID: 2-s2.0-85175172746 OAI: oai:DiVA.org:ltu-101842 DiVA, id: diva2:1807996
Note Validerad;2023;Nivå 2;2023-12-06 (marisr);
Funders: Fujian Provincial Young Top-Notch Talent Plan (MC-201920-X01, Z02101); National Natural Science Foundation of China (51809113, 52171309); Natural Science Foundation of Fujian Province (2021J01843, 2022J06025); Project of Intelligent Situation Awareness System for Smart Ship (MC-201920-X01)
2023-10-302023-10-302024-03-07 Bibliographically approved