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Discrete-time practical robotic control for human-robot interaction with state constraint and sensorless force

Zhiqiang Ma1, Zhengxiong Liu1, Panfeng Huang1

  • 1Research Center for Intelligent Robotics, School of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China; National Key Laboratory of Aerospace Flight Dynamics, Northwestern Polytechnical University, Xi'an 710072, China.

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Summary
This summary is machine-generated.

This study introduces a discrete-time barrier Lyapunov function controller for safer human-robot interaction. It ensures performance and constrains robot movements in complex tasks.

Keywords:
Barrier Lyapunov functionDiscrete-time systemHuman–robot interactionNeural networkState constraint

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Area of Science:

  • Robotics
  • Control Systems Engineering
  • Artificial Intelligence

Background:

  • Controlling continuous-time systems with discrete-time computers degrades performance.
  • Human-robot interaction requires robust control in constrained environments.

Purpose of the Study:

  • To propose a discrete-time barrier Lyapunov function controller for human-robot interaction.
  • To guarantee control performance and ensure state constraints.

Main Methods:

  • Developed a discrete-time barrier Lyapunov function controller.
  • Proved Euler discrete-time stability using a monotonic scaling difference scheme.
  • Utilized analytical synthesis to analyze parameter dependence (sample interval, state constraints).
  • Employed discrete-time neural network estimation for human behavior approximation.

Main Results:

  • Demonstrated guaranteed end-effector state constraints within preset boundaries.
  • Showcased uniform ultimate boundedness of controlled states and estimated forces.
  • Established convergence vicinity dependence on sample interval, uncertainty, and constraints.

Conclusions:

  • The proposed discrete-time barrier Lyapunov function controller effectively manages human-robot interaction in constrained tasks.
  • Numerical simulations and experiments validate the controller's performance and stability.