An adaptive data-based modeling approach for predictive control of batch systems

In this work, we generalize a previously developed data-based modeling methodology for batch processes to account for time-varying dynamics by incorporating online learning ability into the model, making it adaptive. First, the standard recursive least squares (RLS) algorithm with a forgetting factor is applied to update the model parameters. However, applying the standard RLS algorithm leads to a global update of all the models, which may be …