Abstract
This contribution investigates the application of a nonlinear model based adaptive predictive control algorithm to a pH neutralization plant. A local linear model network is responsible for the online identification of the plant. The advantage of such a model is that the information needed by the predictive control algorithm to build gradients is directly available. This aspect reduces the computational cost significantly. Results of real-time control of a laboratory-scale plant are presented.
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