Neural network-based monitoring and control of fluidized bed. Quarterly progress report, October 1, 1995--December 31, 1995

Abstract

This report summarizes work on chaotic behavior control in FBC systems. An update is given to the chaos control method designed to control the chaotic behavior in an FBC system; this method inludes a fully recurrent neural network called the Dynamic System Imitator (DSI). DSI mimics the behavior of a wide variety of dynamic systems in the real world; it was used for modeling linear, nonlinear and chaotic systems, and is also used for iterative prediction of chaotic system behavior. A general methodology for using the DSI to control a nonlinear system is applied to control the chaotic behavior of the Lorenz System. A plan is also outlined for using this method to the FBC system for predicting and controlling its chaotic behavior. Chaotic pressure data from an experimental FBC system was obtained (from METC) on normal and abnormal mixing. Results of chaos analysis applied to these data are presented. These techniques are used to identify the system behavior at different conditions, estimate system order, construct the system attractor, and locate the chaotic behavior in the pressure-drop time series data. Preliminary analysis show that both normal and abnormal conditions of FBC have chaotic characteristics. Objective is to develop a neuro-chaos controller to preserve the normal operational performance of the system.