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.
|Publication status||Published - Jul 2013|
|Event||ECC13 - European Control Conference - Zurich, Switzerland|
Duration: 1 Jul 2013 → …
|Conference||ECC13 - European Control Conference|
|Period||1/07/13 → …|