TY - GEN
T1 - Finite-Time State Estimation of Discrete-Time Linear Systems With Some Extensions. Application to Steering Lateral Vehicle Model
AU - Chaib-Draa, K.
AU - Zemouche, A.
AU - Rajamani, R.
AU - Bedouhene, F.
AU - Laleg-Kirati, Taous-Meriem
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2019
Y1 - 2019
N2 - This paper presents novel exact finite-time estimation algorithms for linear discrete-time systems with extension to singular systems, under specific rank conditions. The proposed estimation algorithms are more general than the well-known deadbeat observers, which can provide finitetime estimation. Two new estimation schemes are proposed; the first scheme provides a direct and explicit estimation algorithm based on the use of delayed outputs, while the second scheme uses two combined asymptotic observers to recover in a finitetime the exact solution of the system. The effectiveness of the developed estimators is shown through application to a steering controlled lateral vehicle system where all states are estimated from look-ahead distance measurement.
AB - This paper presents novel exact finite-time estimation algorithms for linear discrete-time systems with extension to singular systems, under specific rank conditions. The proposed estimation algorithms are more general than the well-known deadbeat observers, which can provide finitetime estimation. Two new estimation schemes are proposed; the first scheme provides a direct and explicit estimation algorithm based on the use of delayed outputs, while the second scheme uses two combined asymptotic observers to recover in a finitetime the exact solution of the system. The effectiveness of the developed estimators is shown through application to a steering controlled lateral vehicle system where all states are estimated from look-ahead distance measurement.
UR - http://hdl.handle.net/10754/662169
UR - https://ieeexplore.ieee.org/document/9029362/
UR - http://www.scopus.com/inward/record.url?scp=85082482191&partnerID=8YFLogxK
U2 - 10.1109/CDC40024.2019.9029362
DO - 10.1109/CDC40024.2019.9029362
M3 - Conference contribution
SN - 9781728113982
SP - 385
EP - 389
BT - 2019 IEEE 58th Conference on Decision and Control (CDC)
PB - IEEE
ER -