Predictor based Self tuning Control of Pressure Plants

Predictor based Self tuning Control of Pressure Plants

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http://dx.doi.org/10.5755/j01.itc.43.4.8742
Abstract. A digital predictor-based self-tuning control with constraints for the pressure plants, which is able to
cope with minimum-phase and nonminimum-phase plant models is presented in this paper. We determined that
applying polynomial factorization for such models the characteristic polynomials of closed-loops are changed.
Therefore, the on-OLQHLGHQWLILFDWLRQRIWKHPRGHOV¶SDUDPHWHUVLVSHUIRUPHGLQDZD\WKDWHQVXUHVVWDEOHFORVHG-loops.
A choice of the sampling period in digital control typically impacts a control quality of the plant, thus we propose a
method for optimization of a sampling period in the digital predictor-based self-tuning control system. The impact of
the selection of the sampling period and input signalV¶constraints ± amplitude boundaries and the change rate - on the
control quality of the pressure plant is experimentally analysed.
Keywords: predictor-based self-tuning control, minimum-phase and nonminimum-phase model, factorization, online identification, closed-loop stability, sampling period optimization, pressure plant.
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Received November 2014.