Chaotic vibration has been identified in the flexible automotive wiper blade at certain wiping speeds. This irregular vibration not only decreases the wiping efficiency, but also degrades the driving comfort. A reliable nonlinear system identification namely nonlinear auto regressive exogenous Elman neural network (NARXENN) was adopted in first stage of this survey to model the flexible dynamics of wiper blade with acquired experimental data. In controller design part, taking into account environmental and external disturbances that cause changes in the dynamic characteristics of the system demanded a robust controller to make a trade off between the worst and best scenario. An active fuzzy force controller (AFLC) supervised by multi objective genetic algorithm (MOGA) is developed to keep both interests of noise and vibration redaction of automobile wiper blade at the reasonable rise time.
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