Читать книгу Nonlinear Filters - Simon Haykin - Страница 38

Observers are dynamic processes, which are used to estimate the states or the unknown inputs of linear as well as nonlinear dynamic systems. This chapter covered the Luenberger observer, the extended Luenberger‐type observer, the sliding‐mode observer, and the UIO. In addition to the mentioned observers, high‐gain observers have been proposed in the literature to handle uncertainty. Although the deployed high gains in high‐gain observers allow for fast convergence and performance recovery, they amplify the effect of measurement noise [40]. Hence, there is a trade‐off between fast state reconstruction under uncertainty and measurement noise attenuation. Due to this trade‐off, in the transient and steady‐state periods, relatively high and low gains are used, respectively. However, stochastic approximation allows for an implementation of the high‐gain observer, which is able to cope with measurement noise [41]. Alternatively, the bounding observer or interval observer provides two simultaneous state estimations, which play the role of an upper bound and a lower bound on the true value of the state. The true value of the state is guaranteed to remain within these two bounds [42].