Knowledge of bed height and solid circulation rate (SCR) is essential to control and improve the performance of circulating fluidized bed systems. In the previous work, a modified 2-region model was developed to calculate the bed height in the standpipe and a Kalman filter algorithm was used to estimate the solid circulation rate. During the SCR estimation process, the initial state space system model is obtained using N4SID algorithm available under the system identification toolbox (SITB) in MATLAB environment. The real data obtained from the test facility of NETL/DOE, Morgantown, West Virginia are utilized for identification purpose. Move air, total riser pressure and riser aeration are used as the inputs to the model and SCR together with all the eight pressures in the standpipe as the outputs. The initial identified system is then transformed to the final model which consists of pressures and SCR as the states and the output contains only pressure variables. Ultimately, Kalman filter is applied to estimate the required SCR state.

In the present work, the number of pressure variables is kept small that is four and this yields almost the same estimation of solid circulation rate as was obtained using eight pressures previously. In addition, another approach to 2-region model has been derived. Finally, the estimated values of SCR along with four pressure drops are used to estimate void fraction, a state variable in one-dimensional dynamic model of standpipe, using sliding mode estimation technique.