Design variable structure fuzzy control based on deep neural network model for servomechanism drive system
نویسندگان
چکیده
This paper presents a new scheme for variable structure (VS) fuzzy PD controller. The rule base of the controller is tuned online. purpose proposed to track accurately preselected position command servomechanism system. Therefore, this study establishes model using black-box modeling approach; simulations were performed based on real-time data collected by LabVIEW and processed MATLAB. input signal driver pseudo-random binary sequence that considers violent excitation in frequency interval. candidate models obtained linear least squares, nonlinear deep neural network (DNN). validation results proved identified DNN has smallest mean square errors. Then, was used design control techniques. A comparison had been executed between VS control, conventional fixed control. experimental confirm can absorb behavior speed regulation test, it reduces rise time from 50% 56%. While continuously changing speed, tracking error (0.412 inches).
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ژورنال
عنوان ژورنال: International Journal of Power Electronics and Drive Systems
سال: 2022
ISSN: ['2722-2578', '2722-256X']
DOI: https://doi.org/10.11591/ijpeds.v13.i4.pp2529-2540