초록 ▼

A hybrid analyzer having a data derived primary analyzer and an error correction analyzer connected in parallel is disclosed. The primary analyzer, preferably a data derived linear model such as a partial least squares model, is trained using training data to generate major predictions of defined ou

A hybrid analyzer having a data derived primary analyzer and an error correction analyzer connected in parallel is disclosed. The primary analyzer, preferably a data derived linear model such as a partial least squares model, is trained using training data to generate major predictions of defined output variables. The error correction analyzer, preferably a neural network model is trained to capture the residuals between the primary analyzer outputs and the target process variables. The residuals generated by the error correction analyzer is summed with the output of the primary analyzer to compensate for the error residuals of the primary analyzer to arrive at a more accurate overall model of the target process. Additionally, an adaptive filter can be applied to the output of the primary analyzer to further capture the process dynamics. The data derived hybrid analyzer provides a readily adaptable framework to build the process model without requiring up-front knowledge. Additionally, the primary analyzer, which incorporates the PLS model, is well accepted by process control engineers. Further, the hybrid analyzer also addresses the reliability of the process model output over the operating range since the primary analyzer can extrapolate data in a predictable way beyond the data used to train the model. Together, the primary and the error correction analyzers provide a more accurate hybrid process analyzer which mitigates the disadvantages, and enhances the advantages, of each modeling methodology when used alone.

대표청구항 ▼

[ What is claimed:] [1.] An apparatus for modeling a process, said process having one or more disturbance variables as process input conditions, one or more corresponding manipulated variables as process control conditions, and one or more corresponding controlled variables as process output conditi

[ What is claimed:] [1.] An apparatus for modeling a process, said process having one or more disturbance variables as process input conditions, one or more corresponding manipulated variables as process control conditions, and one or more corresponding controlled variables as process output conditions, said apparatus comprising:a data derived primary analyzer adapted to sample an input vector spanning one or more of said disturbance variables and manipulated variables, said data derived primary analyzer generating an output based on said input vector;a derivative calculator for computing a derivative of the output of said primary analyzer;an integrator coupled to the output of said derivative calculator for generating a predicted value;an error correction analyzer adapted to sample said input vector, said error correction analyzer estimating a residual between said data derived primary analyzer output and said controlled variables; andan adder coupled to the output of said data derived primary analyzer and said error correction analyzer, said adder summing the output of said primary and error correction analyzers to estimate said controlled variables.