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Predictive controller based on model has been known as a reliable and robust controller in the last 20 years. This paper presents a new idea of design and implementing an adaptive model predictive controller on an industrial “dynamic” and “nonlinear” plant in an integrated software environment using Hysys and Matlab packages. The model predictive controller formation is based on an adaptive state-space...
This paper presents a new methodology to design an instrumentation sensor network for nonlinear processes. The goal is to design a high performance and low price sensor network. The proposed approach utilizes constrained state estimation based on the unscented Kalman filter (UKF) approach to cater for some known signal information which is often either ignored or dealt with heuristically. The approach...
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