Predictive control of integrating processes based on a nonparametric model

The predictive control method presented was developed to assure a stable control of integrating processes that cannot be directly described with bounded weighting sequences. The predictive model is formed on the basis of a differential limited weighting sequence that is identified online. The length...

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Main Authors: Svecko, R., Donlagic, D., Cucej, Z., Debevc, M., Tominc-Bele, L.
Format: Conference Proceeding
Language:English
Subjects:
Adaptive control
Convolution
Nonlinear equations
Optimal control
Predictive control
Predictive models
Process control
Programmable control
Sampling methods
Stress
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creator Svecko, R.
Donlagic, D.
Cucej, Z.
Debevc, M.
Tominc-Bele, L.
description The predictive control method presented was developed to assure a stable control of integrating processes that cannot be directly described with bounded weighting sequences. The predictive model is formed on the basis of a differential limited weighting sequence that is identified online. The length of the predictive horizon, is dependent on process characteristics. A delay, stability, and proportional or integrating process behavior are directly connected with weighting sequence member values. With the delay in a predictive algorithm the influence of nonminimal phase on the control stability was reduced. This means that processes with the nonminimal phase can also be controlled with a one-step predictor.< >
doi_str_mv 10.1109/MELCON.1991.161972
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source IEEE Electronic Library (IEL) Conference Proceedings
subjects Adaptive control
Convolution
Nonlinear equations
Optimal control
Predictive control
Predictive models
Process control
Programmable control
Sampling methods
Stress
title Predictive control of integrating processes based on a nonparametric model
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