Alminde, Lars1; Bendtsen, Jan Dimon2; Stoustrup, Jakob2
1 Aalborg University Space Center, The Technical Faculty of IT and Design, Aalborg University, VBN2 Automation & Control, The Technical Faculty of IT and Design, Aalborg University, VBN3 Center for Model Based Control, The Technical Faculty of IT and Design, Aalborg University, VBN4 Aalborg U Robotics, The Faculty of Humanities, Aalborg University, VBN5 Department of Electronic Systems, The Technical Faculty of IT and Design, Aalborg University, VBN
Model based methods for control of intelligent autonomous systems rely on a state estimate being available. One of the most common methods to obtain a state estimate for non-linear systems is the Extended Kalman Filter (EKF) algorithm. In order to apply the EKF an expression must be available for the Jacobian of the driving function; for complex systems this can be difficult to obtain. This paper presents an EKF variation that makes use of integrated quantised state simulation to propagate the state and obtain a backward difference estimate of the Jacobian at a small computational cost. A simulation case study involving a deep space probe is presented.
Proceedings of the 6th Ifac Symposium on Intelligent Autonomous Vehicles, 2007