TY - GEN
T1 - Nonlinear filtering based on lattice trajectory piecewise linear approximation with application to a wastewater treatment plant
AU - Wang, Jiaming
AU - Xu, Jun
AU - Liu, Jinfeng
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - State estimation is a vital part of state-feedback controller design. The extended Kalman filter (EKF) approximates the original nonlinear system through successive linearization. The linearization points are selected at each sample instant, which is computational complex and may not reflect the overall trend of the nonlinear system. In this paper, we propose a nonlinear filtering method based on lattice trajectory piecewise linear (LTPWL) approximation, named LTPWL-KF, in which the nonlinear system is approximated by the LTPWL model offline, and the online state estimation is then based on the constructed piecewise linear (PWL) system. The boundedness of the variances of the estimation error is proved. A simulation study on a wastewater treatment plant (WWTP) is performed. The results show that the estimation performance of LTPWL-KF is comparable with that of EKF, and the online computational burden of LTPWL-KF is less.
AB - State estimation is a vital part of state-feedback controller design. The extended Kalman filter (EKF) approximates the original nonlinear system through successive linearization. The linearization points are selected at each sample instant, which is computational complex and may not reflect the overall trend of the nonlinear system. In this paper, we propose a nonlinear filtering method based on lattice trajectory piecewise linear (LTPWL) approximation, named LTPWL-KF, in which the nonlinear system is approximated by the LTPWL model offline, and the online state estimation is then based on the constructed piecewise linear (PWL) system. The boundedness of the variances of the estimation error is proved. A simulation study on a wastewater treatment plant (WWTP) is performed. The results show that the estimation performance of LTPWL-KF is comparable with that of EKF, and the online computational burden of LTPWL-KF is less.
KW - Kalman filter
KW - lattice piecewise linear
KW - nonlinear filtering
UR - https://www.scopus.com/pages/publications/85186747333
U2 - 10.1109/ONCON60463.2023.10430759
DO - 10.1109/ONCON60463.2023.10430759
M3 - 会议稿件
AN - SCOPUS:85186747333
T3 - 2023 IEEE 2nd Industrial Electronics Society Annual On-Line Conference, ONCON 2023
BT - 2023 IEEE 2nd Industrial Electronics Society Annual On-Line Conference, ONCON 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2023
Y2 - 8 December 2023 through 10 December 2023
ER -