A Boundary Value Problem Approach to the Optimizationof Chemical Processes Described

An eecient and robust technique for the optimization of dynamic chemical processes is presented. In particular, we address the solution of large, multistage optimal control and design optimization problems for processes described by DAE models of index one. Our boundary value problem approach (a simultaneous solution strategy) is based on a piecewise parametrization of the control functions and a multiple shooting discretization of the DAEs, combined with a speciically tailored SQP technique. The inherent problem structure is exploited on various levels in order to obtain an eecient overall method. In addition, the formulation lends itself well to parallel computation. Unlike other simultaneous strategies based on collocation, direct use is made of existing advanced, fully adaptive DAE solvers. An implementation of this strategy is provided by the recently developed modular optimal control package MUSCOD-II. Apart from a diicult DAE test problem with control and path constraints, two real-life applications of MUSCOD-II are discussed: 1. Optimal control of a fed-batch fermentation process. 2. Optimization of a combustion process in a 1D steady-state tube reactor. The second problem demonstrates the suitability of our approach for the large, stii diierential equation models that are common in chemical kinetics applications. For this problem, we present solutions obtained on a parallel computer.

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