Title :
Stochastic interpretation of H∞ and robust estimation
Author :
Mangoubi, Rami S. ; Appleby, Brent D. ; Verghese, George C.
Author_Institution :
Draper (C.S.) Lab., Cambridge, MA, USA
Abstract :
H∞ and robust estimation methods are discussed from a deterministic as well as a stochastic point of view. The relationship between H∞ and risk sensitivity for systems with known plant dynamics is reviewed. This relationship is extended to the more general case of estimators that are robust to noise and plant model uncertainties. Specifically, it is shown that a stochastic equivalent to the robust H∞ estimator exists. An example is used to compare the estimators in the deterministic sense, using the frequency response of the transfer function between the inputs and the error, as well as in the stochastic sense, using the probability density function of the output error residual
Keywords :
H∞ optimisation; frequency response; identification; probability; transfer functions; uncertain systems; H∞ estimation; frequency response; noise; output error residual; plant model uncertainties; probability density function; risk sensitivity; robust estimation; stochastic interpretation; Aerodynamics; Estimation error; Extraterrestrial measurements; Minimax techniques; Noise measurement; Riccati equations; Robustness; State estimation; Stochastic processes; Stochastic systems;
Conference_Titel :
Decision and Control, 1994., Proceedings of the 33rd IEEE Conference on
Conference_Location :
Lake Buena Vista, FL
Print_ISBN :
0-7803-1968-0
DOI :
10.1109/CDC.1994.411559
