This paper develops a new set-membership estimation algorithm for the identification of time-varying parameters in linear models, where both additive and multiplicative uncertainties are considered explicitly. We show that a recursive algorithm we develop is capable of providing nonconservative approximations to the feasible solution set. Examples are considered to demonstrate the utility and e...

This paper proposes a new set-membership state estimator for estimating the state vector of a nonlinear dynamic robot. The method combines a symbolic technique based on flatness concepts with rigorous numerical methods based on interval analysis. Two testcases related to the state estimation of a sailboat robot are proposed to illustrate the principle and the efficiency of the approach.