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中文摘要：
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，适于在有限作业区问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．
英文摘要：
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.
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S-class functions based adaptive controller design for a class of periodically time-varying nonlinea
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