Finite-level Quantized Iterative Learning Control by Encoding-Decoding Mechanisms

This paper studies the zero-error tacking problem of finite-level quantized iterative learning control using an encoding-decoding method, where both measurement and actuator side quantization and transmission are considered. In particular, the system output is encoded, quantized, transmitted and decoded in sequence for input updating of the next iteration. Then the generated input is transmitted through networks following the same procedure as the output transmission for plant input updating. The zero-error convergence of the proposed scheme is strictly proved and a numerical simulation is provided to demonstrate the effectiveness of the proposed scheme.