<p>This paper proposes an event-triggered fuzzy sampled-data computed-torque control method for robot manipulators to ensure asymptotic trajectory tracking in free space and compliant interaction in contact space. The virtual accelerations in free and contact spaces are unified through a Takagi–Sugeno fuzzy inference mechanism. The computed-torque controller gains are synthesized via linear matrix inequality conditions. Zeno behavior is rigorously ruled out. Numerical simulations of a two-link manipulator demonstrate the effectiveness of the proposed approach.</p>

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Event-Triggered Fuzzy Sampled-Data Position/Force Impedance Control of Robot Manipulators

  • Sung Chul Jee,
  • Ho Jae Lee

摘要

This paper proposes an event-triggered fuzzy sampled-data computed-torque control method for robot manipulators to ensure asymptotic trajectory tracking in free space and compliant interaction in contact space. The virtual accelerations in free and contact spaces are unified through a Takagi–Sugeno fuzzy inference mechanism. The computed-torque controller gains are synthesized via linear matrix inequality conditions. Zeno behavior is rigorously ruled out. Numerical simulations of a two-link manipulator demonstrate the effectiveness of the proposed approach.