Abstract:

Based on active set SQP quasi-sequential approach，a quasi-sequential approach based on primal-dual interior-point method was presented.Quasi-sequential approach included two layers called simulation layer and optimization layer.In the simulation layer orthogonal collocation method was used to discretize both state variables and control variables，and the discretized DAE system was solved at each NLP iteration to eliminate equality constraints and state variables，so that the optimization problem is reduced to a smaller NLP problem only with inequality constraints and control variables.Recent studies showed that interior-point method took advantage of active set method in large-scale optimization problems，thus in the optimization layer a primal-dual interior-point method is employed.FORTRAN is used to code quasi-sequential approach and a distillation optimal control problem is optimized to demonstrate the efficiency.Results show that this approach has the capacity to solve large-scale dynamic optimization problems