A neural network approach for on-line parameter estimation in unknown or poorly known processes with a time delay is proposed. The case of plants with unknown time delay and/or steady state gain has been considered. The main result of the paper is the analytical proof of the weight distribution as a sampling centred on the correct value of the time delay. Such a property, along with the estimation of the steady-state gain of the process from the sum of the weights, leads to an accurate identification of the unknown parameters of a process with time delay. A practical application of such a result is the design of an adaptive Smith controller. Simulation results are included in the paper to illustrate the proposed technique.

On-line process estimation by ANNs and Smith controller design

LANDI, ALBERTO
1998-01-01

Abstract

A neural network approach for on-line parameter estimation in unknown or poorly known processes with a time delay is proposed. The case of plants with unknown time delay and/or steady state gain has been considered. The main result of the paper is the analytical proof of the weight distribution as a sampling centred on the correct value of the time delay. Such a property, along with the estimation of the steady-state gain of the process from the sum of the weights, leads to an accurate identification of the unknown parameters of a process with time delay. A practical application of such a result is the design of an adaptive Smith controller. Simulation results are included in the paper to illustrate the proposed technique.
1998
A., Balestrino; F., BINI VERONA; Landi, Alberto
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/53106
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