中文摘要：

传感器饱和是控制系统中较为常见的一种物理约束.本文针对一类含饱和输出的受限系统,提出了两种学习控制算法.具体而言,首先,对于重复运行的被控系统,设计了开环P型迭代学习控制器,实现在有限时间区间内对期望轨迹的完全跟踪,并在λ范数意义下分析了算法的收敛性,给出了含饱和输出的迭代学习控制系统的收敛条件.进而,针对期望轨迹为周期信号的被控系统,提出了闭环P型重复学习控制算法,并分析了这类系统的收敛性条件.最后,通过一个仿真实例验证了本文所提算法的有效性.

英文摘要：

Sensor saturation is a common physical constraint in control systems.Two learning control algorithms are proposed in this research for a class of linear systems with saturated output.Specifically,an open-loop P-type iterative learning controller is first designed for repetitive operating systems to ensure entire tracking in limited interval,and the convergence condition is derived by employing λ norm analysis.Furthermore,for controlled systems with periodic desired trajectory,the asymptotic tracking condition of closed-loop P-type repetitive learning control technique is deduced as well.Finally,the simulation results show the effectiveness of the proposed algorithms.