A Comparison of Two Methods for State Estimation: A Statistical Kalman Filter, and a Deterministic Interval-Based Approach

In an uncertain framework the performance of two methods of state estimation for discrete-time linear systems are compared on a pedagogical example. The first one is the well known Kalman filter, which is accurate when the measurement noises and the state disturbances are assumed Gaussian white noises and their statistical properties are available. The second one is a set-membership state estimator, which is also based on the...