Data Based Prediction and Control of a Non-Linear Process

Provided by: Research In Motion
Topic: Big Data
Format: PDF
Real time non-linear processes consists of disturbances and noise, which makes it difficult to control the quality of the end product. Actuated by this the authors present a simple data based prediction and control technique to improve the product quality. The strategy involves modeling by system identification using N4SID method and Model Predictive Control (MPC) is designed to control the process variable, which enhance the outcome of the product. This method is applied on a raw milling process and the performances are compared with the conventional controllers.

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