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Fault isolation for nonlinear dynamic systems based on parameter intervals

The study of fault detection and isolation for nonlinear dynamic systems has been receiving significant attention. Up to now few literatures pay attention to the speed of fault isolation. However, it is a crucial problem for the design of the fault-tolerant control (FTC) of the nonlinear dynamic systems. In this article a new method of fault isolation for nonlinear dynamic systems is proposed. The method is based on the monotonous characteristic of the prediction error of the observer with respect to singular parameter difference between the system and the observer. The proposed method has the advantage of the methods based on adaptive observers that fits a large kind of nonlinear dynamic systems, while it does not have their disadvantage that take a long time to identify the system parameter: Therefore the fault isolation of this method is quicker. The performance of the method is illustrated by simulation results using a nonlinear dynamic model of an alcoholic fermentation process.