动力定位船轨迹跟踪鲁棒自适应容错控制

本文研究了输入饱和状态下的动力定位船故障容错鲁棒自适应控制问题.该问题以动力定位船轨迹跟踪任务为目标,提出了一种新颖的鲁棒自适应控制器的设计,并且引入了二阶快速非奇异终端滑模和神经网络控制算法保证了控制器在实际任务中的执行效果.首先,介绍了三自由度动力定位船的运动模型包括了运动学模型和动力学模型以及推进器故障模型.然后,设计了二阶快速非奇异终端滑模面,提出了一种针对时变扰动和模型不确定性的鲁棒控制方案,保证系统无抖振现象的前提下实现了系统更快的收敛速度.同时运用被动容错控制思想,确保动力定位船在推进器故障发生时依然能够实现预计的跟踪性能.此外,通过Lyapunov稳定性判据分析,证明了提出的改进自适应滑模控制方法可确保系统在初始状态未知前提下,跟踪误差渐近收敛于零.最后,通过数值仿真实验结果验证了控制律的有效性.

Robust adaptive fault-tolerant tracking control for dynamic positioning vessel

This paper investigates the problem of fault-tolerant robust adaptive control for dynamic positioning vessel with input saturation. It aims at the trajectory tracking task of dynamic positioning vessel. A novel robust adaptive controller is proposed for the tracking task of the dynamic positioning vessel by incorporating second-order fast nonsingular terminal sliding mode (SOFNTSM) and neural network (NN) control algorithm into design which ensure the execution effect of the controller in actual tasks. Firstly, a three-degree-of-freedom surface vessel model , including kinematics, dynamics and the actuator fault model, is introduced. By introducing the SOFNTSM manifold, we propose a robust control scheme in presence of time-varying disturbances and model uncertainty to achieve a faster convergence rate without chattering phenomenon. Subsequently, with the aid of passive fault-tolerance control, the tracking performance can be guaranteed when actuator fault occurs. In addition, the Lyapunov stability criterion proves that the proposed improved adaptive sliding mode control method can ensure that the tracking error asymptotically converges to zero under the premise that the initial state is unknown. Finally, the control design is validated by experimental results conducted using numerical simulations.