Hybrid predictor, hybrid prediction method, and system for and m

Data processing: generic control systems or specific application – Generic control system – apparatus or process – Optimization or adaptive control

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700 45, 700 29, 700 31, G05B 1302

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06064916&

ABSTRACT:
A hybrid predictor for predicting the output of a process, and a hybrid prediction method using the hybrid predictor. Also, a system for and a method of controlling a process using the hybrid predictor and hybrid prediction method are provided. In order to obtain a shifted prediction vector and step response coefficients, the hybrid predictor uses a parameter model which can be updated in accordance with a variation in the process. The control method includes the steps of predicting process output signals generated in a prediction horizon, based on input signals applied to the process, correcting the predicted values, based on output signal values measured at the next scan, comparing the corrected prediction value with a reference value to derive an error vector, calculating a control signal to minimize the error vector, and applying the control signal to the process. The hybrid predictor is characterized by an addition of a model parameter estimator and a model response converter. In this hybrid predictor, a prediction vector, which is indicative of the length of a prediction horizon, is directly calculated. Accordingly, it is possible to reduce a required memory capacity while updating model response coefficients in accordance with a variation in the process by the model parameter estimator. Thus, an adaptive prediction can be achieved.

REFERENCES:
patent: 5568378 (1996-10-01), Wojsznis
patent: 5740033 (1998-04-01), Wassick et al.
patent: 5796609 (1998-08-01), Tao et al.
Jay H. Lee et al., "State-space Interpretation of Model Predictive Control", Pergamon, Brief Paper, pp. 707-717, Date unknown.

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