UNIFIED APPROACH TO SOLVING OPTIMAL DESIGN-CONTROL PROBLEMS IN BATCH DISTILLATION

This article presents a unified approach to simultaneous solution of optimization and optimal control problems in batch distillation, operating under different modes of operation: variable, constant, or optimal reflux. The simplified, computationally efficient short-cut method and a novel algorithm to solve the optimal control problems in batch distillation is the basis of this unified approach. The short-cut method identifies the feasible region of operation essential for optimization and optimal control problems, and provides analytical partial derivatives of the model parameters crucial to the solution. The new algorithm for the solution of optimal control problems is a combination of the maximum principle and NLP optimization techniques. It circumvents the problems associated with the maximum principle approach (iterative solution of a two-point boundary value problem, unbounded control variables, and inability to handle the simultaneous optimization and optimal control problem), and the coupled ODE discretization-NLP optimization scheme for nonlinear models (higher system nonlinearities, multiplicity of solutions, sensitivity of convergence to initial guesses). This algorithm reduces the dimensionality of the problem, and the nature of the algorithm allows a common platform to optimal solutions of different operating conditions. This article also shows that different categories of the optimal control problems in batch distillation essentially involve the solution of the maximum distillate problem.