A resource saving FPGA implementation approach to fractional Kalman filter. Issue 13 (8th June 2022) - Xu, Bo; Bai, Libing; Chen, Kai; Tian, Lulu
Abstract: The efficiency of the hardware implementations of fractional Kalman filter (FKF) heavily relies on the efficiency of realising the fractional‐order derivative operator. In this paper, a generic software and hardware implementation of the FKF based on the Grunwald–Letnikov approximation is proposed and verified on a field‐programmable gate array. The main advantage of this particular realisation is its resource saving capability on both software and hardware components (e.g. digital signal processing chips), and this enables fast and efficient real‐time computation of the FKF. Furthermore, the performance of the FKF is evaluated via studying the mean square boundedness of the filtering error. At last, a mass‐spring‐damper example is implemented via Matlab simulations to verify the applicability of the proposed approach and moreover, a hardware experiment is also conducted to demonstrate the advantage of resource saving.