Fuzzy neural network vibration control on a piezoelectric flexible hinged plate using stereo vision detection

Abstract

Vibration control on a two-connected piezoelectric flexible hinged plate is investigated, using a fuzzy neural network algorithm based on binocular vision measurement. As for vision sensing, a method to acquire vibration signals of the low frequency bending and torsional mode is investigated. To damp out the residual vibration quickly, the fuzzy neural network is applied to ensure the stability and control effect adaptively. To verify the stereo vision measurement method and the applied controller, an experimental setup of the piezoelectric flexible hinged plate with a binocular stereo vision is constructed. Experiments are conducted by using the binocular stereo vision measurement system and the adopted controller. The experimental results demonstrate the feasibility of the visual measurement method. Furthermore, the designed fuzzy neural network can attenuate the bending and torsional vibrations quickly, in comparison with proportional and derivative control, particularly for the small-level residual vibration.