Minimum Time Dynamic Optimization of Grade Transition in TE Process Using a Novel Incremental Evolutionary Programming

So far, many studies focus on the grade transition of polyolefin, and polyolefin grade transition optimization was solved by Sequential Quadratic Programming (SQP) or Iterative Dynamic Programming (IDP) traditionally. In this paper，to solve the problem of grade transition, we build a two layers of grade transition control structure . The two layers are loop control layer and grade transition layer. It is transformed into a constrained nonlinear programming problem by control variable parameters. We propose a novel Incremental Evolutionary Algorithm (IEA) which is similar to the evolutionary programming to solve this problem. Meanwhile, a Double Layer Optimization Algorithm (DLOA) is adapted to solve the minimum time dynamic optimization problem. In DLOA, the inner optimization is to search the feasible region in the given final time (tf); and in the outer layer, tf is reduced according to certain laws; finally, we get minimal tf and optimal trajectories of control variables.