Fault detection of Discrete-Event Systems based on an identified timed model

Abstract

In this paper, a method for fault detection of Discrete-Event Systems (DES) based on a timed model called Timed Automaton with Outputs and Conditional Transitions (TAOCT), obtained by identification, is presented. The TAOCT is an extension of a recent untimed model proposed in the literature, called Deterministic Automaton with Outputs and Conditional Transitions (DAOCT). Differently from the DAOCT, where only the logical behavior of the DES is considered, the TAOCT takes into account information about the time that the events are observed, and, for this reason, it can be used for the detection of faults that cannot be detected by using untimed models, such as faults that lead the fault detector to deadlocks. The TAOCT represents the fault-free system behavior, and a fault is detected when the observed behavior is different from the one predicted by the model, considering both logical and timing information. A practical example is used to illustrate the results of the paper.

Decentralized Fault Detection and Fault-Tolerant Control for Nonlinear Interconnected Systems

“…x i ∈ is the estimated state of the i-th subsystem. In order to avoid the influence of modeling uncertainty and noise and other factors on the system model, f N i (x i ) and g N i (x i ) in nominal model Equation ( 2) are used to replace f i (x i ) and g i (x i ) in Equation (1) in the estimator model Equation (7). Satisfying [27], which can better track the state vector x i by adjusting the size of λ i .…”

“…In the model-based method [3], the system's mathematical model and sensor measurement values are mainly used to detect faults. The literature [4][5][6][7] are model-based analysis methods. Model-based schemes also utilize many different ways, such as using adaptive estimators [8,9], fuzzy observers [10], high-gain observers [11], neural network observers [12] and geometric techniques [13], as Processes 2021, 9, 591 2 of 17 well as using the state estimator as a reference model for fault detection.…”

Variable step control to improve scanning speed of gene sequencing stage

“…Especially when the feedforward controller highly matches with the controlled object, high-speed and high-precision control effects can be achieved. Around this idea, the Jerk derivative feedforward control was proposed, 9 which was further imposed on the acceleration feedforward to compensate for the low-frequency component of the servo error caused by the high-order resonance term. Another Jerk feedforward control with adjustable damping factor was employed to obtain better feedforward performance by adjusting the damping factor for different input trajectories.…”