Two-dimensional incremental recursive least squares identification for batch processes

Abstract

In this paper, two-dimensional incremental recursive least squares identification methods for batch processes are proposed. First, parameter increment along the time direction is introduced to represent the batch process, which changes slowly along the batch direction in comparison with the parameters. Then, we apply RLS method along the batch direction to derive two kinds of two-dimensional incremental recursive identification algorithm, which can use the latest estimation results along both the time direction and batch direction to obtain the new estimated value. By extending the model assumption from parameter batch-invariant to parameter increment batch-invariant, this method can effectively accelerate the convergence rate. Furthermore, the convergence property of the proposed method is established by the associated ordinary differential equation method. Finally, we demonstrate the superiority of the proposed identification method in two case studies.