Moving horizon estimation and control of a binary simulated moving bed chromatographic processes with Langmuir isotherms

Abstract

Simulated moving bed chromatographic (SMB) chromatographic processes are widely used for separations in pharmaceutical and biotechnological industries. In the present work, the control of such processes is proposed based on a semi-centralized control scheme that utilizes a combination of model predictive control (MPC) and classical PID control. The necessary information from the process, i.e. the internal concentration profiles, for the MPC is obtained by a moving horizon estimator (MHE) in real-time from the available limited measurements (the cycle-averaged concentrations of the extract and raffinate product streams and the dimensionless retention times of the concentration waves in the regeneration zones). As a test case study, the separation of a hypothetical system governed by the Langmuir isotherms in the nonlinear concentration range of the isotherms is considered. First, the stand-alone MHE is validated in open loop mode with no plant-model mismatch under deterministic and stochastic conditions. In the latter case, the true measurements are subject to random normally distributed noise. To evaluate the performance of the proposed control strategy, a reference tracking (change of the requirements for both the purities and the retention times) scenario is simulated. The investigated scenarios are: (i) no plant-model mismatch, (ii) MHE with ideal noiseless measurements and finally (iii) MHE under the influence of measurement noise. Results show that the controller is able to follow the change of the references from reduced purity to complete separation and vice versa closely.