基于转筒速率调节的帆式船舶自适应跟踪控制OA

[Objective]Amid energy and environmental challenges,sail-assisted ships are key to low-car-bon shipping.Marine disturbances and communication limits degrade their path-following performance.This work proposes an adaptive tracking algorithm for rotor-sail ships.Utilizing the Magnus effect,it achieves high propulsion efficiency,simple structure and good adaptability.[Methods]First,a modified guidance law is constructed by improving the traditional logic virtual ship(LVS)guidance principle.This improvement in-volves the incorporation of an intervention method based on a finite boundary circle,effectively reducing the communication load of the guidance system.The modified guidance law ensures that when the vessel enters the coverage area of the boundary circle,the guidance signal is no longer updated,thus preventing unneces-sary signal transmission and conserving communication resources.Meanwhile,to address the issue of actuator input saturation,a saturation compensation function is integrated into the guidance law,which helps to ensure that the system remains within operational limits of the actuators,thus enhancing the robustness of the control system.Secondly,radial basis function(RBF)neural networks are employed for online approximation of sys-tem uncertainties.The RBF neural networks can respond in real time to changing dynamic conditions,thereby providing an effective mechanism to compensate for unmodeled dynamics or external disturbances that may affect the vessel's tracking trajectory.To avoid the"explosion of computational complexity"inherent in tradi-tional backstepping control,dynamic surface control(DSC)technique is introduced.This technique simplifies the control law by using first-order filters,which significantly reduces the computational burden and prevents the growth of intermediate variables that would otherwise increase computational complexity.Furthermore,a robust adaptive control algorithm is designed by combining neural damping and adaptive techniques.This is coupled with an integral event-triggered mechanism,which is particularly important in dealing with slight fluc-tuations in system states.Traditional event-triggered mechanisms,which rely on instantaneous state measure-ments,may fail to trigger updates in cases of minor state fluctuations,leading to long periods without signal updates,thus degrading the system's closed-loop performance.The proposed integral event-triggered mecha-nism can effectively avoid long periods of non-triggering caused by minor state fluctuations.Its triggering ef-fect is more natural and efficient,thus significantly reducing the frequent transmission of control commands and mechanical wear of actuators.Finally,the stability of the proposed control algorithm is rigorously ana-lyzed using Lyapunov theory to guarantee that all error signals are semi-global uniform and ultimately bound-ed(SGUUB).To validate the proposed control strategy,numerical simulations are conducted in MATLAB,where marine environmental disturbance under a sea state level of 4 is simulated based on the NORSOK wind spectrum and the JONSWAP wave spectrum.[Results]The results of simulations demonstrate that the pro-posed algorithm significantly enhances the path following performance of sail-assisted vehicles.The proposed algorithm exhibits high control accuracy and fast response,maintaining the position and heading errors within ranges of 3 meters and 5 degrees,respectively.Notably,due to the introduction of the event-triggered mecha-nism and servo systems,the control inputs remain within the allowable range of actuator operations and signal chattering is significantly reduced,effectively minimizing mechanical wear on actuators.Additionally,the adaptive laws embedded in the control algorithm demonstrate effective convergence,ensuring that the system can reach a stable operating condition despite dynamic disturbances present in the marine environment.The utilization of the proposed sail-assisted navigation strategy can achieve an 11.6%improvement in propulsion efficiency under a sea state level of 4,substantially reducing energy consumption and promoting sustainable maritime operations.[Conclusions]The path following performance of the proposed system exhibits not only low communication load but also strong robustness,making it suitable for practical deployment in mar-itime navigation.The findings provide a practical and feasible technical pathway for green transformation of marine vessels,contributing to development of more sustainable and energy-efficient shipping technologies.Therefore,the proposed control algorithm and sail-assisted strategy could play a vital role in advancing future of green maritime transportation.