Prof. Dr. Zhenhua Wang 

State estimation of a dynamic system is crucial for many applications, e. g. estimating the

states of batteries is pivotal in optimizing battery performance and prolonging battery lifetime.

The ubiquitous uncertainties and nonlinear system dynamics bring challenges to state

estimation. Set-membership estimation methods, which can effectively deal with bounded

uncertainties, provide a practical solution to state estimation of uncertain dynamic systems.

However, set-membership estimation for nonlinear systems has not been well addressed. Most

existing set-membership estimation methods for nonlinear systems are complex and have

heavy computational burdens. This project aims to develop straightforward and efficient setmembership

estimation methods for nonlinear dynamic systems with bounded uncertainties.

First, the real system will be modeled as a nonlinear parameter-varying system representation

to bridge the gap between linear design theories and the nonlinear system dynamics. Second, a

two-step methodology integrating robust observer design and zonotopic analysis will be used to

develop straightforward and efficient set-membership estimation methods. Third, the slowly

varying characteristics of some disturbances will be used to improve estimation accuracy.

Finally, the proposed methods will be validated on a battery platform in Universität Oldenburg.

The obtained results will provide solutions to some practical estimation problems such as

battery state-of-charge estimation.