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  • 1.
    Andersson, Jan-Erik
    et al.
    Linköping University, Department of Mechanical Engineering. Linköping University, The Institute of Technology.
    Johansson, Gert
    Linköping University, Department of Mechanical Engineering. Linköping University, The Institute of Technology.
    Robot control for wood carving operations2001In: Mechatronics (Oxford), ISSN 0957-4158, E-ISSN 1873-4006, Vol. 11, no 4, p. 475-490Article in journal (Refereed)
    Abstract [en]

    The aim of this paper is to implement sensor control in wood carving operations. The introduction of wood carving is a step towards the development of a new manufacturing method for the wood manufacturing industry, where wood carving would facilitate increased freedom of the design choice. A control method that improves robot control and supports simpler programming, based on using an industrial robot equipped with a wrist mounted force/torque-sensor. is proposed for the wood carving process. This paper describes the structure and control algorithm of the system and how different machining parameters affect the cutting forces. The evaluation of the system showed that it is possible to control the cutting depth at speeds up to 7.5 mms by adjusting the rake angle of the tool to obtain a nominal force.

  • 2.
    Carvalho Bittencourt, André
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Saarinen, Kari
    ABB Corporate Research, Västerås, Sweden.
    Sander Tavallaey, Shiva
    ABB Corporate Research, Västerås, Sweden.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology. ABB Robotics, Västerås, Sweden.
    A data-driven approach to diagnostics of repetitive processes in the distribution domain: Applications to gearbox diagnosticsin industrial robots and rotating machines2014In: Mechatronics (Oxford), ISSN 0957-4158, E-ISSN 1873-4006, Vol. 24, no 8, p. 1032-1041Article in journal (Refereed)
    Abstract [en]

    This paper presents a data-driven approach to diagnostics of systems that operate in a repetitive manner. Considering that data batches collected from a repetitive operation will be similar unless in the presence of an abnormality, a condition change is inferred by comparing the monitored data against an available nominal batch. The method proposed considers the comparison of data in the distribution domain, which reveals information of the data amplitude. This is achieved with the use of kernel density estimates and the Kullback–Leibler distance. To decrease sensitivity to disturbances while increasing sensitivity to faults, the use of a weighting vector is suggested which is chosen based on a labeled dataset. The framework is simple to implement and can be used without process interruption, in a batch manner. The approach is demonstrated with successful experimental and simulation applications to wear diagnostics in an industrial robot gearbox and for diagnostics of gear faults in a rotating machine.

  • 3.
    Olofsson, Bjorn
    et al.
    Lund University, Sweden.
    Nielsen, Lars
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
    Path-tracking velocity control for robot manipulators with actuator constraints2017In: Mechatronics (Oxford), ISSN 0957-4158, E-ISSN 1873-4006, Vol. 45, p. 82-99Article in journal (Refereed)
    Abstract [en]

    An algorithm for high-performance path tracking for robot manipulators in the presence of model uncertainties and actuator constraints is presented. The path to be tracked is assumed given, and the nominal trajectories are computed using, for example, well-known algorithms for time-optimal path tracking. For online path tracking, the nominal, feedforward trajectories are combined with feedback in a control architecture with a secondary controller, such that robustness to uncertainties in model or environment is achieved. The control law is based on existing path-velocity control (PVC), or so called online time scaling, but in addition to speed adaptation along the tangent of the path, the algorithm also comprises an explicit formulation and approach, with several attractive properties, for handling the deviations along the transversal directions of the path. For achieving fast convergence along the normal and binormal directions of the path in 3D motion, the strategy proposed has inherent exponential convergence properties. The result is a complete architecture for path-tracking velocity control (PTVC). The method is evaluated in extensive simulations with manipulators of different complexity, and PTVC exhibits superior performance compared to PVC. (C) 2017 Elsevier Ltd. All rights reserved.

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