A soft constraint adjustment method based on multi-parametric programming in steady-state target calculation for model predictive control

In order to track the result of local economic optimization, steady-state target calculation for Model Predictive Control should be implemented. When steady-state target calculation for Model Predictive Control becomes infeasible, soft constraints adjustment is involved to make it feasible. The traditional method does not consider that different soft constraints adjustment will affect final economic objective achievement, It is not guaranteed to achieve the optimal economic objective through soft constrains adjustment by choosing different weighted coefficient according to experience, a multi-parametric programming algorithm is proposed to divide the variation range of coefficients of the soft constraint into different regions. It can determine the most suitable soft constraints adjustment to achieve optimal economic objective by comparing economic objective value in the different region. Simulation results of typical control model of a heavy oil fractionator proposed by Royal Dutch/Shell Group showed the effectivity of the proposed algorithm.