An optimization method based on mnemonic enhancement for solving data reconciliation problems

作者：Zhang Zheng Jiang; Shao Zhi Jiang^*; Chen Xi; Fang Xue Yi; Wang Ke Xin; Qian Ji Xin

来源：Journal of Chemical Engineering of Chinese Universities, 2011, 25(3): 482-488.

• Complex Processes
• Convergence
• Data reconciliation
• Mnemonic enhancement
• Optimization method
• Problem-based
• Rigorous model
• Separation process

Data reconciliation problem based on rigorous model of a complex process system is a large scale nonlinear programming (NLP) problem with large degrees of freedom. NLP solvers could be inefficient to solve this kind of problems and sometimes hard to converge. In view of that the data reconciliation problem should be solved repeatedly based on the same model when the feed condition changes, a mnemonic enhancement based method was proposed to solve the problem efficiently. The proposed method uses the experience of pervious solutions to improve convergence. The frame of this method was designed and the procedure of implementation was presented. The application of this method to simulate the multi-column system and ethylene separation process system demonstrates the effectiveness of this method.

• 出版日期2011
• 单位浙江大学