基于神经网络的系统优化与参数估计集成研究（ISOPE）方法
ALGORITHMS OF INTEGRATED SYSTEM OPTIMIZATION AND PARAMETER ESTIMATION (ISOPE) BASED ON NEURAL NETWORK
-
摘要: 提出了两种基于神经网络（NN）改进的系统优化与参数估计集成（ISOPE）稳态优化算法，其中利用动态信息建立动态NN模型用于过程稳态优化．目的是为了克服ISOPE算法对真实过程的摄动，减少ISOPE算法设定点变动次数，充分利用过程动态信息．仿真结果验证了两种改进算法的优越性和有效性．Abstract: This paper proposes two modified algorithms of ISOPE based on neural network(NN).In order to avoid perturbation on the real process and decrease the number of setpoint changes,dynamic informa- tion is fully used to identify the dynamic NN model,which is applied in steady-state optimization of industrial processes.The results of simulation show that the two modified algorithms are effective.
下载:
