Cubature H∞ information filter

This paper presents a state estimation algorithm referred to as a cubature H
∞
information filter (CH
∞
IF) for nonlinear systems. The proposed algorithm is developed from a cubature Kalman filter, an H
∞
filter and an extended information filter. The CH
∞
IF is a derivative free filter, where the information state vector and information matrix are propagated rather than the state vector and error covariance matrix. Furthermore, the CH
∞
IF is extended for multi-sensor state estimation. The efficacy of the CH
∞
IF is demonstrated by a simulation example of a permanent magnet synchronous motor in the presence of Gaussian and non-Gaussian noises.