船舶航向控制的多滑模鲁棒自适应设计

针对带有未知虚拟控制增益和常参数不确定的非匹配不确定船舶航向非线性控制问题,设计了一种新的多滑模鲁棒自适应控制算法.该算法利用神经网络来逼近系统模型的不确定性;应用逐步递推的多滑模控制算法降低了控制器的复杂性;尤其是采用Nussbaum函数处理系统中符号未知的问题,避免了可能存在的控制器奇异值问题;然后借助Lyapunov稳定性分析方法,理论分析证明了所得闭环系统全局一致最终有界,且跟踪误差收敛到零.仿真试验结果表明,该方法具有较好的控制效果.

Multiple-sliding-mode robust adaptive design for ship course tracking control

A new multiple sliding mode robust adaptive control algorithm is proposed for mismatched uncertain ship steering nonlinear mathematic model with unknown virtual control coefficient and constant parameter uncertainty. By employing radial based function neural network to approximate uncertain nonlinear system functions, and by combining multiple sliding mode control with recursive technique and Nussbaum gain approach, the algorithm can not only simplify the complexity of the controller and eliminate the need for a priori knowledge of the control gain sign to be known, but also overcome the possible controller singularity problem. Based on the Lyapunov function, the stability analysis shows that all closed loop signals are global uniformly ultimately bounded, with the tracking error converging to zero. Finally, simulation results are presented to show that the controller design has better effectiveness.