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- W1982315313 abstract "Consideration is given to data-based dynamic modelling and positioning of a pneumatic servo-actuator with time delay due to friction and air compressibility. A Smith predictor-type control scheme is considered to improve the control behaviour. System non-linearity is verified by the inability of linear modelling to provide satisfactory prediction. Data based dynamic modelling is undertaken using the group method of data handling (GMDH) neural network, a feedforward type neural network, and the techniques show potential for prediction of non-linear behaviour. Hence the time delay effect to the closed-loop control can be removed by incorporating the trained nonlinear model as a predictor in the feedback path. Conventional feedback control with/without the predictor are compared, and it is shown that the time delay system stability is significantly improved by using the non-linear predictor. The effect of time delay is most significant at small stroke changes of fast response demand and experiments were undertaken around the mid-stroke, which is less damped than any other position." @default.
- W1982315313 created "2016-06-24" @default.
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- W1982315313 date "2002-01-01" @default.
- W1982315313 modified "2023-09-23" @default.
- W1982315313 title "POSITION CONTROL OF A PNEUMATIC SERVOACTUATOR WITH TIME DELAY USING A NEURAL NETWORK PREDICTOR" @default.
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- W1982315313 doi "https://doi.org/10.5739/isfp.2002.637" @default.
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