摘要
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.
A new multiple-sliding-mode robust adaptive control algorithm is proposed for a nonlinear mismatched uncertain ship steering model with unknown virtual control coefficients and constant parameter uncertainty.By employ-ing the radial based function neural network to approximate nonlinear uncertain system functions,and by combining the multiple-sliding-mode control with recursive technique and Nussbaum gain approach,the algorithm not only simplifies the complexity of the controller and eliminates the need of the a priori knowledge of the sign in the control gain,but also overcomes 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 proposed method is more effective than existing methods.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2010年第12期1618-1622,共5页
Control Theory & Applications
基金
国家自然科学基金资助项目(60974136)
关键词
船舶操纵
参数不确定性
滑模变结构控制
神经网络
自适应
ship maneuvering
parameter uncertainty
sliding mode variable structure control
neural network
adaptive
