Cascade Process Modeling with Mechanism-Based Hierarchical Neural Networks

Abstract: Cascade process, such as wastewater treatment plant, includes many nonlinear subsystems and many variables. When the number of sub-systems is big, the input-output relation in the first block and the last block cannot represent the whole process. In this paper we use two techniques to overcome the above problem. First we propose a new neural model: hierarchical neural networks to identify the cascade process. Then we use serial structural mechanism model based on the physical equations to connect with neural model. A stable learning algorithm and theoretical analysis are given. Finally, this method is used to model a wastewater treatment plant. Real operational data of wastewater treatment plant is applied to illustrate the modeling approach.

• Type: Journal
• Year: 2010
• Where: IJNS
• Authors: Qiumei Cong, Wen Yu, Tianyou Chai
• Keywords: Cascade Process, IJNS 2010, Neural Model, Wastewater Treatment Plant