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Trajectory Tracking Control of a Real Redundant Manipulator of the SCARA Type

  • Urrea, Claudio (Automation Group, Department of Electrical Engineering, University of Santiago of Chile) ;
  • Kern, John (Automation Group, Department of Electrical Engineering, University of Santiago of Chile)
  • 투고 : 2014.04.22
  • 심사 : 2015.09.01
  • 발행 : 2016.01.01

초록

Modeling, control and implementation of a real redundant robot with five Degrees Freedom (DOF) of the SCARA (Selective Compliant Assembly Robot Arm) manipulator type is presented. Through geometric methods and structural and functional considerations, the inverse kinematics for redundant robot can be obtained. By means of a modification of the classical sliding mode control law through a hyperbolic function, we get a new algorithm which enables reducing the chattering effect of the real actuators, which together with the learning and adaptive controllers, is applied to the model and to the real robot. A simulation environment including the actuator dynamics is elaborated. A 5 DOF robot, a communication interface and a signal conditioning circuit are designed and implemented for feedback. Three control laws are executed in: a simulation structure (together with the dynamic model of the SCARA type redundant manipulator and the actuator dynamics) and a real redundant manipulator of the SCARA type carried out using MatLab/Simulink programming tools. The results, obtained through simulation and implementation, were represented by comparative curves and RMS indices of the joint errors, and they showed that the redundant manipulator, both in the simulation and the implementation, followed the test trajectory with less pronounced maximum errors using the adaptive controller than the other controllers, with more homogeneous motions of the manipulator.

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피인용 문헌

  1. Conceptual design and kinematic analysis of a novel parallel robot for high-speed pick-and-place operations 2017, https://doi.org/10.1007/s11465-018-0471-4
  2. Parameter identification methods for real redundant manipulators vol.15, pp.4, 2017, https://doi.org/10.1016/j.jart.2017.02.004
  3. Research of manipulator trajectory tracking based on adaptive robust iterative learning control pp.1573-7543, 2018, https://doi.org/10.1007/s10586-018-1919-3
  4. Robust trajectory tracking control for uncertain mechanical systems: servo constraint-following and adaptation mechanism pp.1366-5820, 2018, https://doi.org/10.1080/00207179.2018.1528386