Published March 2021 | Version v1
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Event-based neural network predictive controller application for a distillation column

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In this work, the case study is a distillation column, which is a multi-input multi-output (MIMO) nonlinear process. An event-based neural network predictive controller is utilized for the case study, considering control and energy policies. Computation and communication reduction are the main purposes of the event-based strategy. The event-based model predictive controller also copes successfully with the multi-input multi-output (MIMO) time-delayed nonlinear processes. In order to achieve a suitable nonlinear data-based model of the process, an event-based neural network predictive controller is proposed. Moreover, new Cuckoo Optimization Algorithm (COA) is employed to improve the efficiency of the neural network. Evaluation of the proposed controller has illustrated a satisfactory performance in both setpoint tracking and disturbance rejection while computational load has been significantly decreased

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