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A circulating fluidized bed (CFB) has been applied to a wide variety of chemical industry processes to reduce pollution and increase efficiency. Identifying the state and the bed height in the standpipe of the CFB is required for designing a controller to improve the system. A Kalman filter algorithm has been used to successfully estimate the state and the bed height of the stand-pipe in the cold flow circulating fluidized bed (CFCFB). However, for some oscillated cases, this method is not performing well. In addition, covariance matrices Q and R need to be assumed initially and depending upon initial values, the estimator behaves unstable for some cases. In this research, an H;∞ estimation algorithm is applied to estimate the state, and the bed height of the standpipe in CFCFB. This H;∞ method only requires one variable for tuning to have proper estimation of the state and the bed height. Test results show that using H;∞ method, the state estimation is improved over the Kalman filter.