工业过程稳态随机优化理论研究与算法

Theory & Algorithm for Stochastic Steady-State Optimizing Control in Industrial Processes

本文对工业过程稳态优化问题在有有随机噪声的情况下进行理论上的研究,提出了随机系统稳态的概念和随机稳态优化的最优解的概念,并且提出一种基于方差分析的二次近似次优算法,证明了该算法的最优性和收敛性,仿真验证了该算法比原有方法更有效。

In this paper, the theory of stochastic steady-state optimizing control is discussed, the steady-state opncept of a stochastic industrial process is proposed and a second order approximation algorithm is set up based on variance analysis. The optimality and convergence of the new algorithm are proved. Simulation results illustrate that the new algorithm is more effective than others.