摘要
为了研究船舶航向非线性系统的自适应自动舵跟踪控制问题,采用T-S模糊系统逼近模型不确定性,将动态面控制与最少学习参数算法结合,提出了一种自适应模糊跟踪控制算法.该算法学习参数少、计算量小,易于工程实现;并且能够避免可能存在的控制器奇异值问题.同时,该算法保证了闭环系统的稳定性,能够使得航向跟踪误差任意小.仿真结果验证了控制器的有效性.
A problem of an adaptive control design of a ship autopilot system was considered for a ship with rudder dynamics.By employing a T-S fuzzy system to approximate uncertain functions,an adaptive fuzzy control algorithm was developed based on a dynamic surface control（DSC） and minimal learning parameter（MLP） algorithm.With fewer learning parameters and reduced computation load,the proposed algorithm can be conveniently implemented in applications,and can avoid the possible controller singularity problems.In addition,the boundedness stability of the closed-loop system is guaranteed and the tracking error can be made arbitrarily small.Simulation results validate the effectiveness and the performance of the proposed scheme.
出处
《哈尔滨工程大学学报》
EI
CAS
CSCD
北大核心
2012年第1期9-14,共6页
Journal of Harbin Engineering University
基金
国家自然科学基金资助项目(60874056
51179019)
中国博士后科学基金特别资助项目(200902241)
辽宁省自然科学基金资助项目(20102012)
关键词
船舶
航向自动舵
模糊控制
动态面控制
最少学习参数算法
ship
autopilot
fuzzy control
dynamic surface control（DSC）
minimal learning parameter（MLP） algorithm
