Brunovsky Decomposition for Dynamic Interval Localization

This paper proposes a new set-membership method for estimating the trajectories of dynamical systems, when states are completely unknown and only non-linear observations available. The first part proposed is symbolic follows decomposition Brunovsky, i.e. , it decomposes set differential equations describing system into two blocks constraints: one block gathers analytical that do not involve operators, while other composed linear chains integrators. second method, relies on decomposition, numerical based contractor approach. It involves specific optimal operator narrowing sets feasible solutions. approach shown to be efficient difficult problem dynamic localization mobile robot, without any prior knowledge about its states.