A timed extension of the discrete-event systems failure diagnosis approach of [1], [2], is proposed. The diagnoser is a timed automaton, constructed off-line, from a timed automaton system model. The construction procedure is illustrated through a practical example. A notion of Δ-diagnosability for timed languages, is defined. Necessary and sufficient conditions linking Δ-diagnosability, to the structure of a constructed diagnoser are given.
We propose an online diagnosis approach for a class of hybrid systems. The normal and the faulty behaviors of the system are modeled with rectangular hybrid automata. Our approach is based on the use of a diagnosis procedure which performs, online, an estimation of the system states, within a given time window, and based on the current record of observable timed events. Each new estimation can be triggered either, by a new event observation, or simply by the elapse of time. We give examples to illustrate the use of our hybrid systems diagnosis approach.
This paper investigates the diagnosability of Rectangular Hybrid Automata used for modeling a class of hybrid systems. First, a generalized definition of Limited-Time Lookahead diagnosability of timed languages, for multiple failure modes, is proposed. Then, we provide a systematic approach, for checking the LTLa diagnosability of systems modeled with Rectangular Hybrid Automata, and verifying some realistic assumptions. A practical example is considered throughout the paper for illustration purposes.
We propose an online diagnosis approach for a class of hybrid systems. The normal and the faulty behaviors of the system are modeled with rectangular hybrid automata. Our approach is based on the use of a diagnosis procedure which performs, online, an estimation of the system states, within a given time window, and based on the current record of observable timed events. Each new estimation can be triggered either, by a new event observation, or simply by the elapse of time. We give examples to illustrate the use of our hybrid systems diagnosis approach.
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