2015 | OriginalPaper | Buchkapitel
Predictive Control of a Multivariable Neutralisation Process Using Elman Neural Networks
verfasst von : Antoni Wysocki, Maciej Ławryńczuk
Erschienen in: Progress in Automation, Robotics and Measuring Techniques
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This paper presents development and simulation results of a computationally efficient predictive control algorithm based on a recurrent Elman neural network. The considered process is a multivariable neutralisation reactor. Process modelling and control issues are thoroughly discussed. In particular, the discussed computationally efficient predictive control algorithm with on-line trajectory linearisation and quadratic optimisation is compared to the truly nonlinear scheme with nonlinear optimisation repeated of each sampling instant on-line.