Multibatch Model Predictive Control for Repetitive Batch Operation with Input–Output Linearization

Abstract

Because of the repetitive nature of the batch process, in conventional batch process control, the start of the subsequent batch is often assumed to be the same as that of the prior batch. Nevertheless, in real operation, under the influence of various exterior factors, most batch processes involve gradual changes over batches and, thus, the end-point condition would affect the start of the subsequent process batch. The initial condition at each batch may not be reset to be the desired initial condition. In order to ensure an optimum operation, it is essential to taking into account the effect of the previous batch. In this paper, a multibatch dynamics model is derived. It takes into account this batchwise dynamics. The derived process model can provide the benefits of better prediction and performance. In order to overcome the problem of nonlinearity in the batch process, the nonlinear process is transformed to a linear process through input–output feedback linearization. The identification method of the ...