Low‐complexity ISS state estimation approach with bounded disturbances
Qiang Shen, Jieyu Liu, Xiaogang Zhou, Qian Zhao, Qi Wang · International Journal of Adaptive Control and Signal Processing · 2018
Summary This paper presents a low‐complexity input‐to‐state stable ellipsoidal outer‐bounding state estimation approach with unknown but bounded disturbances. The bounds on the noise are specified by ellipsoids. The feasible set is updated through computing the Minkowski sum and intersection of two ellipsoids. At the observation stage, the observation noise bounding ellipsoid is replaced by a parallelotope containing it. Then, each observation update is transformed into multiple consecutive iterations to intersect ellipsoid with strips, which significantly reduces its per‐update computational complexity. Furthermore, an adaptive selection scheme of the parameters is derived to ensure the stability of the estimation error. As a result, the proposed approach entails stability and delivers a trade‐off between performance and complexity.