输出重定义下的非线性非最小相位系统迭代学习控制  

Output-redefinition-based iterative learning control for nonlinear non-minimum phase systems

作　　者：陈冰玉[1] 孙明轩[1] 朱胜[1] 

机构地区：[1]浙江工业大学信息工程学院,浙江杭州310023

出　　处：《控制理论与应用》2010年第7期948-952,共5页Control Theory & Applications

基　　金：国家自然科学基金资助项目(60474005;60774021;60874041)

摘　　要：讨论非线性非最小相位系统实现完全跟踪的迭代学习控制方法,适于在有限作业区间上重复运行的受控系统.在控制器设计时,通过输出重定义以使非最小相位系统的零动态变成渐近稳定特性.分别采用部分限幅和完全限幅两种学习算法设计控制器,理论分析表明两种算法能够保证学习系统中所有变量的有界性和跟踪误差在整个作业区间上渐近收敛于零.数值仿真验证了两种迭代学习控制系统的跟踪性能.An iterative learning control is presented for nonlinear non-minimum phase systems. The systems undertaken are assumed to perform the same tasks repeatedly. Output redefinition is carded out and the zero-dynamics with respect to the redefined output exhibit a stable behavior. Both methodologies of partially saturated and fully saturated learning are adopted in designing the learning controllers. Stability and convergence of the learning systems are established, ensuring the zero-convergence of the tracking error and the boundedness of all variables in the closed-loop. Numerical results are presented for demonstrating the effectiveness of the proposed two learning control methods.

关 键 词：非最小相位系统 输出重定义 迭代学习控制 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]