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  • 1.
    Feng, Lei
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Centres, Innovative Centre for Embedded Systems, ICES.
    Wonham, W. M.
    On the Computation of Natural Observers in Discrete-Event Systems2010In: Discrete event dynamic systems, ISSN 0924-6703, E-ISSN 1573-7594, Vol. 20, no 1, p. 63-102Article in journal (Refereed)
    Abstract [en]

    Natural projections with the observer property have proved effective in reducing the computational complexity of nonblocking supervisory control design, and the state sizes of the resulting controllers. In this paper we present an algorithm to verify this property, or if necessary to achieve it. A natural projection is a special type of general causal reporter map; for the latter an algorithm is already known for verification and modification. This algorithm could be used to verify the observer property of a natural projection, but if the natural projection is not an observer the algorithm is not applicable to modify it to an observer. Also, while a general reporter map always admits a unique smallest refinement with the observer property, a natural projection does not. Indeed there may exist several minimal extensions to the original observable event set of a natural projection. We show that the problem of finding a minimal extension is NP-hard, but propose a polynomial-time algorithm that always finds an acceptable extension. While not guaranteed to be minimal, it is in practice often reasonably small.

  • 2. Zhang, Huimin
    et al.
    Feng, Lei
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Machine Design (Div.). KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Embedded Control Systems. KTH, School of Industrial Engineering and Management (ITM), Centres, Innovative Centre for Embedded Systems, ICES. KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.
    Li, Zhiwu
    Control of Black-Box Embedded Systems by Integrating Automaton Learning and Supervisory Control Theory of Discrete-Event Systems2019In: IEEE Transactions on Automation Science and Engineering, ISSN 1545-5955, E-ISSN 1558-3783, p. 1-14, article id 10.1109/TASE.2019.2929563Article in journal (Refereed)
    Abstract [en]

    The paper presents an approach to the control of black-box embedded systems by integrating automaton learning and supervisory control theory (SCT) of discrete-event systems (DES), where automaton models of both the system and requirements are unavailable or hard to obtain. First, the system is tested against the requirements. If all the requirements are satisfied, no supervisor is needed and the process terminates. Otherwise, a supervisor is synthesized to enforce the system to satisfy the requirements. To apply SCT and automaton learning technologies efficiently, the system is abstracted to be a finite-discrete model. Then, a C* learning algorithm is proposed based on the classical L* algorithm to infer a Moore automaton describing both the behavior of the system and the conjunctive behavior of the system and the requirements. Subsequently, a supervisor for the system is derived from the learned Moore automaton and patched on the system. Finally, the controlled system is tested again to check the correctness of the supervisor. If the requirements are still not satisfied, a larger Moore automaton is learned and a refined supervisor is synthesized. The whole process iterates until the requirements hold in the controlled system. The effectiveness of the proposed approach is manifested through two realistic case studies.

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