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In many ILC algorithms, nonlinear input uncertainties such as saturation, dead-zone and hysteresis, which do exist due to practical implementations, are always ignored. Although various ILC algorithms have been proposed to compensate various nonlinear input uncertainties, a systematic design framework is still missing. This note presents a unified design framework to deal with very general nonlinear...
Iterative Learning Control (ILC) is a practical control methodology which can “learn” from the experience gained from past iterations. ILC has been widely used in many industrial repetitive processes and has shown its potential in achieving perfect tracking performance. This paper focuses on time-varying cascade systems with two sub-systems. An ILC algorithm is available for each sub-system to ensure...
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