基于非线性规划的间歇反应过程动态优化算法

Dynamic optimal algorithm for batch processes based on nonlinear programming

采用对数障碍法和外点法将实际间歇反应过程中的约束条件转化为惩罚项生成新的目标函数,将有约束优化问题转化为无约束优化问题;采用非线性规划算法中的操作变量参数化方法,将操作变量的最优解转化为操作变量子函数的线性组合,将无限维最优解问题转化为有限维权值向量的最优估计问题;同时应用Lyapunov理论设计一种动态迭代优化算法,重点讨论了采样时间的取值对优化算法收敛性的影响。最终用于解决靛蓝生产中碱熔间歇反应过程中过程参数的最优分布,从而提高目标产物的最终收率和降低生产成本等。通过碱熔间歇反应动态优化问题作为实例进行仿真试验,实验结果表明所述算法的有效性和可靠性。

The log barrier method and external point method are used to deal with the constraints of actual batch process and transform the constrained optimization problem into the unconstrained optimization problem.Using control vector parameterization of nonlinear programming algorithm,the optimal profiles of manipulated variables are approximated by a set of algebraic equations,and then the optimal control problem with infinite dimensions is converted into an optimal estimation problem with finite dimensions using a trial function with unspecified coefficients.A dynamic iterative optimization algorithm is designed based on Lyapunov theory and the effect of sampling time on the convergence of optimization algorithm is discussed emphatically.At last,the dynamic optimal algorithm is used to solve the optimal distribution of process parameters in alkali fusion batch reaction process,which can increase the ultimate yield of target products and reduce production costs.Simulation experiment was carried out,and the results show the effectiveness and reliability of the proposed algorithm.