The paper presents a nonlinear unknown input observer (NUIO) based on singular value decomposition aided reduced dimension\nCubature Kalman filter (SVDRDCKF) for a special class of nonlinear systems, the nonlinearity of which is only caused by part of its\nstates. Firstly, the algorithmof general NUIO is discussed and the unknown input observer based on singular value decomposition\naidedCubatureKalman filter (SVDCKF) given.Thena special nonlinear systemmodel with unknown input is introduced. Based on\nthe proposed model and the corresponding NUIO, the equivalent integral form with partial sampling and all sampling of the state\nvector in Cubature Kalman filter is analyzed. Finally the nonlinear unknown input observer based on singular value decomposition\naided reduced dimension Cubature Kalman filter is obtained. Simulation results show that the proposed algorithm can meet the\nrequirements of the system and ismore important to increase the calculating efficiency a lot, although it has a decline in the accuracy\nof the filter.
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