TY - JOUR
T1 - Semidefinite programming solutions to robust state estimation problem with model uncertainties
AU - Ratnarajah, T.
AU - Luo, Z. Q.
AU - Wong, K. M.
PY - 1998/12/1
Y1 - 1998/12/1
N2 - In this paper, a novel finite-horizon, discrete-time, time-varying state estimation method is proposed based on the recent robust semidefinite programming (RSDP) technique. The proposed formulation guarantees a robust performance with respect to model uncertainties which are known to lie within certain a priori bounds. This is in contrast to earlier robust designs, such as H∞, which accommodate all conceivable uncertainties and therefore lead to overly conservative solutions.
AB - In this paper, a novel finite-horizon, discrete-time, time-varying state estimation method is proposed based on the recent robust semidefinite programming (RSDP) technique. The proposed formulation guarantees a robust performance with respect to model uncertainties which are known to lie within certain a priori bounds. This is in contrast to earlier robust designs, such as H∞, which accommodate all conceivable uncertainties and therefore lead to overly conservative solutions.
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M3 - Conference article
AN - SCOPUS:0032268009
VL - 1
SP - 275
EP - 276
JO - Proceedings of the IEEE Conference on Decision and Control
JF - Proceedings of the IEEE Conference on Decision and Control
SN - 0191-2216
T2 - Proceedings of the 1998 37th IEEE Conference on Decision and Control (CDC)
Y2 - 16 December 1998 through 18 December 1998
ER -