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Open access Jul 2026

Robust higher-order feedback feedforward ILC for networked nonlinear system with varying trial lengths, data dropouts and disturbances.

A robust higher-order feedback feedforward ILC framework is developed that simultaneously handles varying trial lengths and independent random packet dropouts in both the sensor and actuator channels to compensate for the missing tracking information induced by iteration-varying trial lengths.

Hao Chen, Can Tian, Yun-Bo Wang et al. · 0 citations
Open access Jul 2026

Robust Iterative Learning Control with Higher-Order Feedback for Variable-Trial-Length Nonlinear Systems Under Input Saturation and Disturbances

The proposed method uses input and error information from several previous trials to compensate for the loss of learning information caused by non-uniform trial lengths and ensures the rigorous asymptotic convergence of the anticipated error to zero.

Jinyi Chen, Hao Chen, Can Tian et al. · 0 citations

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