Fast Particle Filters and Their Applications to Adaptive Control in Change-Point ARX Models and Robotics

Abstract

The Kalman filter has provided an efficient and elegant solution to control problems in linear stochastic systems. For nonlinear stochastic systems, control problems become much more difficult and a large part of the literature resorts to linear approximations so that an "extended Kalman filter " or a "mixture of Kalman filters " can be used in place of the