抽象的

State Estimation by Discrete Reduced Order UI Observer and Discrete Kalman Filter for Linear Systems

M.S. Das, S. K. Singh

In this paper unknown input observer using projection operator method is used to estimate five states of the fifth order lateral axis model of L-1011 system in discrete domain. Discrete reduced order UI observer is used to estimate the states of the system in noiseless and noisy environment. Kalman filter has been designed to estimate the state of L-1011 system when noise is considered. Finally error between the actual and estimated states of the system by UI observer and Kalman filter i.e performance of both are compared. It has been shown that Kalman filter is good estimator than UI observer in noisy environment in respect of estimation. The simulations have been done using MATLAB and SIMULINK Toolbox & the results of the simulations have been displayed in this paper.