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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.
    Lian, Binbin
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.).
    Tao, Sun
    Tianjin University.
    Yimin, Song
    Tianjin University.
    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.
    Elasto-dynamicoptimization of a 5-DoF parallel kinematic machine considering parameteruncertainty2019In: IEEE/ASME transactions on mechatronics, ISSN 1083-4435, E-ISSN 1941-014X, no 1, p. 315-325Article in journal (Refereed)
  • 3.
    Svensson, Lars
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.
    Masson, Lola
    Mohan, Naveen
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.
    Ward, Erik
    KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL.
    Pernestål Brenden, Anna
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Machine Design (Div.). KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL.
    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.
    Törngren, Martin
    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, Superseded Departments (pre-2005), Machine Design. KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.
    Safe Stop Trajectory Planning for Highly Automated Vehicles: An Optimal Control Problem Formulation2018In: 2018 IEEE Intelligent Vehicles Symposium (IV), IEEE, 2018, p. 517-522Conference paper (Refereed)
    Abstract [en]

    Highly automated road vehicles need the capabilityof stopping safely in a situation that disrupts continued normaloperation, e.g. due to internal system faults. Motion planningfor safe stop differs from nominal motion planning, since thereis not a specific goal location. Rather, the desired behavior isthat the vehicle should reach a stopped state, preferably outsideof active lanes. Also, the functionality to stop safely needs tobe of high integrity. The first contribution of this paper isto formulate the safe stop problem as a benchmark optimalcontrol problem, which can be solved by dynamic programming.However, this solution method cannot be used in real-time. Thesecond contribution is to develop a real-time safe stop trajectoryplanning algorithm, based on selection from a precomputedset of trajectories. By exploiting the particular properties ofthe safe stop problem, the cardinality of the set is decreased,making the algorithm computationally efficient. Furthermore, amonitoring based architecture concept is proposed, that ensuresdependability of the safe stop function. Finally, a proof of conceptsimulation using the proposed architecture and the safe stoptrajectory planner is presented.

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