Abstract：A signal bounded iterative learning control algorithm is designed to address the input saturation constraint and convergence time interval setting problem of second-order nonlinear systems. Using inequality transformation to separate unknown parameter functions in the system, establish a limited amplitude iterative learning algorithm to estimate unknown parameter functions; By means of the predefined time convergence conversion function, the arbitrary initial value sliding mode surface is converted into a new variable with zero initial value, and a variable gain limiting iterative learning controller is constructed. Strict theoretical analysis proves that the sliding mode surface converges to zero after finite iterative learning and all signals of the closed-loop system are uniformly bounded,ensuring the trajectory tracking error converges within the preset time. The numerical simulation of arbitrary initial value robot trajectory tracking control verifies the effectiveness of the proposed method and the excellent characteristics of the convergence time interval that can be set according to engineering requirements.
殷春武. 非线性系统的跟踪时间可预设迭代学习控制[J]. 复杂系统与复杂性科学, 2026, 23(3): 112-120.
YIN Chunwu. Iterative Learning Control with Preset Tracking Time for Nonlinear Systems[J]. Complex Systems and Complexity Science, 2026, 23(3): 112-120.
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