IEEE Access (Jan 2024)

Non-Intermittent Sampled-Data Consensus of Networked Euler-Lagrange Systems Using Dynamic Scaling Without Neighbors’ Velocity Measurement

  • Yang Li,
  • Yilin Wang,
  • Pengfei Zhang,
  • Yuehuan Zhang

DOI
https://doi.org/10.1109/ACCESS.2024.3479324
Journal volume & issue
Vol. 12
pp. 152730 – 152737

Abstract

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This paper proposes a non-intermittent control scheme for the consensus of multiple Euler-Lagrange systems under sampled-data communication without using neighbors’ velocities. In the current pulse-modulated control method, the control torques have to be zero at all sampling instants, making the control intermittent. As an upgrade to the pulse-modulated control method, the main characteristic of this scheme is that the control torques of the Euler-Lagrange systems are non-intermittent, which benefits many real-world applications. To achieve non-intermittent control torques, the dynamic scaling function is introduced to replace the pulse function of the previous works. The main feature of the dynamic scaling function is that it transitions into the next sampling interval and is non-zero at the sampling instant. This feature ensures non-intermittent control torques for the Euler-Lagrange systems. Necessary and sufficient consensus conditions are established with dramatically greater complexity and difficulty in mathematical derivation. It is shown that the shape of the dynamic scaling functions also influences consensus in addition to its integral. Finally, numerical examples show that the proposed dynamic scaling control scheme exhibits smooth and non-intermittent control torques and ensures consensus under the consensus conditions.

Keywords