To solve trajectory tracking problem of switched system with sensor saturation, an iterative learning control algorithm is proposed. The method uses actual measurement error to modify the control variable of system on the premise that switched rule does not change along iteration axis, but it randomly changes along time axis. Moreover, by dealing with the saturation via diagonal matrix method, the convergence of the algorithm is strictly proved in the sense of λ-norm, and the convergence condition is derived. The algorithm can achieve complete tracking of desired trajectory in the finite time interval under the random switched rule, as iterations increase. The simulation example verifies the validity of the proposed algorithm.

中文翻译：

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具有传感器饱和约束的开关系统的迭代学习控制

针对传感器饱和切换系统的轨迹跟踪问题，提出了一种迭代学习控制算法。该方法在切换规则不沿迭代轴变化，而是沿时间轴随机变化的前提下，利用实际测量误差来修正系统的控制变量。此外，通过对角矩阵法处理饱和度，严格证明了该算法在λ-范数意义上的收敛性，并推导出收敛条件。随着迭代次数的增加，该算法可以在随机切换规则下的有限时间间隔内实现对期望轨迹的完整跟踪。仿真实例验证了所提出算法的有效性。