Tight Remainder-Form Decomposition Functions with Applications to Constrained Reachability and Interval Observer Design

This paper proposes a tractable family of remainder-form mixed-monotone decomposition functions that are useful for over-approximating the image set of nonlinear mappings in reachability and estimation problems. In particular, our approach applies to a new class of nonsmooth nonlinear systems that we call either-sided locally Lipschitz (ELLC) systems, which we show to be a superset of locally Lipschitz continuous systems, thus expanding the set of systems that are formally known to be mixed-monotone. In addition, we derive lower and upper bounds for the over-approximation error and show that the lower bound is achievable with our proposed approach. Moreover, we develop a set inversion algorithm that along with the proposed decomposition functions, can be used for constrained reachability analysis and interval observer design for continuous and discrete-time systems with bounded noise.