Bounded Switched Linear Estimator for Smooth Nonlinear Systems

The problem of establishing hard bounds on the state estimate of a nonlinear system using a switching piecewise linear hybrid estimator is addressed. Within an operating region, the proposed hybrid estimator uses a variant of the extended set-membership filter to select piecewise linear models based on minimizing uncertainty. Under certain conditions, analysis shows that the error between the center of the estimated set and the true value is bounded. A priori selection of the base piecewise linear models to guarantee a level of uncertainty is achieved by optimizing the placement of operating points over the operating region. The proposed methods are applied to a complex aircraft example to show its applicability