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The system uncertainty analysis is based on entropy.
Fuzzy set theory is used to encode system uncertainty in a structural reliability analysis.
The open loop transfer function is identified and the system uncertainty is calculated.
A generalized and automated process for the evaluation of system uncertainty using computer simulation is presented.
The actuator failure, modeling error, and aerodynamic parameters perturbation are viewed as the lumped system uncertainty.
In the proposed design, load changes are treated as a system uncertainty in the LMI approach.
The proposed technique allows robust fault diagnosis under suitable conditions on the system uncertainty.
Furthermore, only one direct neural network (NN) is employed for the lumped system uncertainty approximation.
However, the design of DSMC is more challenging because its sliding variable contains an unknown system uncertainty.
The system uncertainty is parametrized by a unknown parameter vector, which is absorbed in the parametrization of disturbances.
To achieve robustness against system uncertainty and variation of parameters, a linear matrix inequality (LMI) based approach is employed.
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