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This work addresses the model-based control of the Tennessee-Eastman (TE) challenge problem using a state-shared model. A detailed mechanistic nonlinear model is developed and validated with data taken from the original Downs and Vogel work [Downs, J. J.; Vogel, E. F. Comput. Chem. Eng. 1993, 17 (3), 245-255] and their accompanying Fortran programs. Two plantwide model predictive control (MPC) strategies that differ in the types of models used are applied to address regulation and transition control. The first employs multiple fixed-parameter models, identified at known grades, and the second uses an adaptive state-shared model Hoo, K. A. Comput. Chem. Eng. 2003, 27 (11), 1641-1656] constructed from three fixed-parameter models and one specialized adaptive model. The first MPC strategy demonstrates closed-loop regulation and grade-transition performance especially when the worst disturbance, the loss of the A feed, is present. The second MPC strategy provides a better closed-loop performance for grade transitions when compared with the first MPC strategy.

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