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Fuzzy neural network vibration control on a piezoelectric flexible hinged plate using stereo vision detection
摘要： 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.
关键词： Piezoelectric flexible hinged plate,binocular vision measurement,experiments,vibration control,fuzzy neural network algorithm
更新于2025-09-23 15:22:29
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[IEEE 2019 20th International Conference of Young Specialists on Micro/Nanotechnologies and Electron Devices (EDM) - Erlagol (Altai Republic), Russia (2019.6.29-2019.7.3)] 2019 20th International Conference of Young Specialists on Micro/Nanotechnologies and Electron Devices (EDM) - Determination of the Approach to the Construction of the Neural Network Algorithm for Detection of Emergency and Pre-Emergency Situations by Multicriterial Electro-Optical System
摘要： Determination of the approach to the construction of the neural network algorithm for detection of emergency and pre-emergency situations by multicriterial electro-optical system was performed. The analysis for forecasting and recognition of situations in the coal mine is carried out. Two approaches on forecasting of situations – autoregression and neural networks are analyzed. The advantages of neural networks to forecasting of situations were determined. Two approaches on recognition of situations: on dynamics of change concentration of one gas and on ratios of the several gases concentration are analyzed. Classification of situations in the coal mine is formulated. Admissible concentration was define for methane – up to 2%, carbon oxide – up to 0.0017%, carbon dioxide – 1%, coal dust of 150 mg/m3. The limiting concentrations for situations in coal mine are calculated. It is proposed to use MatLab for modeling neural network. Approach to creation of neural network algorithm for forecasting situation in coal mine is proposed. Structure of the neural network for forecasting situation in the coal mine is developed.
关键词： multicriterial electro-optical system,neural network algorithm,monitored parameters,forecasting
更新于2025-09-11 14:15:04