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Adaptive observers for linear stochastic time‐variant systems with disturbances
Author(s) -
Perabò Stefano,
Zhang Qinghua
Publication year - 2009
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.1051
Subject(s) - a priori and a posteriori , control theory (sociology) , observer (physics) , state (computer science) , set (abstract data type) , computer science , disturbance (geology) , mathematics , linear system , fault detection and isolation , stochastic process , algorithm , control (management) , artificial intelligence , statistics , paleontology , mathematical analysis , philosophy , physics , epistemology , quantum mechanics , actuator , biology , programming language
Motivated by fault detection and isolation problems, we present an approach to the design of state observers for linear time‐variant stochastic systems with unknown parameters and disturbances. The novelties with respect to more conventional techniques are as follows: (a) the joint estimation of state, disturbances and parameters can be carried out; (b) it is a full‐stochastic approach: the unknown parameters and disturbances are random quantities and prior information, in terms of means and covariances, can be easily taken into account; (c) the observer structure is not fixed a priori , rather derived from the optimal one by means of a sliding window approximation; (d) contrary to descriptor system techniques, which estimate the state starting from a restricted set of disturbance‐free equations, our approach is focused on disturbance estimation, from which state estimates are derived straightforwardly. Copyright © 2008 John Wiley & Sons, Ltd.