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What is Quantized DDILC for Nonlinear Systems about?

This paper presents two novel quantized data driven iterative learning control (QDDILC) algorithms for nonlinear systems affected by sensor saturation and data quantization. The algorithms are designed to improve tracking performance using previous iteration data, proving that sensor saturation does not alter convergence properties but may slow the rate. The study establishes convergence conditions that do not rely on complete system model information, allowing for effective control with limited data resour

Author

Furqan Memon

Language

EN