Machines (Sep 2022)

Discrete-Time Adaptive Decentralized Control for Interconnected Multi-Machine Power Systems with Input Quantization

  • Junxiong Ge,
  • Mengyun Wang,
  • Haimin Hong,
  • Jinyu Zhao,
  • Guowei Cai,
  • Xiuyu Zhang,
  • Pukun Lu

DOI
https://doi.org/10.3390/machines10100878
Journal volume & issue
Vol. 10, no. 10
p. 878

Abstract

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This study contrives a discrete-time adaptive decentralized control algorithm with input quantization for interconnected multi-machine power systems with SVC. First, a dynamic surface scheme is applied to the excitation controller design, in which first-order digital low-pass filters are used to predict the next virtual control law, which overcomes the model conversion problem in backstepping. Therefore, the controller design and structure are simplified. Further, an improved hysteresis quantizer is utilized for amplitude quantization of control input signals; along with the discretization of time, this achieves digital decentralized control. Finally, semi-global uniformly ultimately boundedness (SGUUB) of the whole control system is demonstrated based on the Lyapunov stability theory, and the effectiveness of the proposed control algorithm is verified on the ModelingTech real-time simulation experimental platform for power electronics.

Keywords