TY - GEN
T1 - Smooth Variable Structure Filter for pneumatic system identification
AU - Al-Shabi, Mohammad
AU - Saleem, Ashraf
AU - Tutunji, Tarek A.
PY - 2011
Y1 - 2011
N2 - The Smooth Variable Structure Filter (SVSF) is a newly-developed predictor-corrector filter for state and parameter estimation [1]. The SVSF is based on the Sliding Mode Control concept. It defines a hyperplane in terms of the state trajectory and then applies a discontinuous corrective action that forces the estimate to go back and forth across that hyperplane. The SVSF is suitable for fault detection and identification applications because of its stability and robustness in modeling uncertainties. The SVSF has two indicators of performance; the a posteriori output error and the chattering. The latter as a signal-contains the system's information which is proven and explored in this paper. The SVSF is applied for the identification of pneumatic systems in order to verify the proposed method. Furthermore, the proposed method is compared with neural network and the results reveal that SVSF is better in identifying nonlinear systems.
AB - The Smooth Variable Structure Filter (SVSF) is a newly-developed predictor-corrector filter for state and parameter estimation [1]. The SVSF is based on the Sliding Mode Control concept. It defines a hyperplane in terms of the state trajectory and then applies a discontinuous corrective action that forces the estimate to go back and forth across that hyperplane. The SVSF is suitable for fault detection and identification applications because of its stability and robustness in modeling uncertainties. The SVSF has two indicators of performance; the a posteriori output error and the chattering. The latter as a signal-contains the system's information which is proven and explored in this paper. The SVSF is applied for the identification of pneumatic systems in order to verify the proposed method. Furthermore, the proposed method is compared with neural network and the results reveal that SVSF is better in identifying nonlinear systems.
KW - Pneumatic Systems
KW - Smooth Variable Structure Filter
KW - System Identification
UR - http://www.scopus.com/inward/record.url?scp=84857219925&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84857219925&partnerID=8YFLogxK
U2 - 10.1109/AEECT.2011.6132500
DO - 10.1109/AEECT.2011.6132500
M3 - Conference contribution
AN - SCOPUS:84857219925
SN - 9781457710841
T3 - 2011 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies, AEECT 2011
BT - 2011 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies, AEECT 2011
T2 - 2011 1st IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies, AEECT 2011
Y2 - 6 December 2011 through 8 December 2011
ER -