Abstract:

In the optimal design and control of preparative chromatographic processes, the obstacles appear when one tries to link the Wilson’s framework of chromatographic theories based on partial differential equations (PDEs) with the Eulerian presentation to optimal control approaches based on discrete time states, such as Markov decision processes (MDP) or Model predictive control (MPC). In this paper, the 0-1 model is presented to overcome the obstacles for nonlinear transport chromatography (NTC). With the Lagrangian-Eulerian description (L-ED), one solute cell unit is split into two solute cells, one (SCm) in the mobile phase with the linear velocity of the mobile phase, and the other (SCs) in the stationary phase with zero-velocity. The thermodynamic state vector, Sk, which comprises four vector components, i.e., the sequence number, the position and the local solute concentrations in both SCms and SCses, is introduced to describe the local thermodynamic path (LTP) and the macroscopical thermodynamic path (MTP). For the NTC, the LTP is designed for a solute zone to evolve from the state, Sk, to the virtual migration state, SM, undergoing the virtual net migration sub-process, and then to the state, Sk+1, undergoing the virtual net inter phase mass transfer sub-process in a short time interval. Complete thermodynamic state iterations with the Markov characteristics are derived by using the local equilibrium isotherm and the local lumped mass transfer coefficient. When the local thermodynamic equilibrium is retained, excellent properties, such as consistency, stability, conservation, accuracy, etc., of the numerical solution of the 0-1 model are observed in the theoretical analysis and in the numerical experiments of the nonlinear ideal chromatography. It is found that the 0-1 model could properly link up with the MDP or optimal control approaches based on discrete time states.

Key words: Lagrangian-Eulerian description, Markov decision processes , nonlinear transport chromatography, nonlinear chromatography