IEEE Access (Jan 2018)

Robust Adaptive Neural Prescribed Performance Control for MDF Continuous Hot Pressing System With Input Saturation

  • Liangkuan Zhu,
  • Yugang Zhou,
  • Yaqiu Liu

DOI
https://doi.org/10.1109/ACCESS.2018.2800778
Journal volume & issue
Vol. 6
pp. 9099 – 9113

Abstract

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This paper presents a novel nonlinear control approach for medium-density fiberboard continuous hot pressing electro-hydraulic servo system (EHSS). The EHSS is subject to input saturation and unknown external disturbance. The approach is developed in the framework of the prescribed performance control design. The transient and steady behaviors are both considered by virtue of an appropriate performance function. A new robust adaptive neural control algorithm is then developed by introducing a dynamic surface control scheme. Moreover, the compensation control is designed for the nonlinear term arising from the input saturation. It is shown with the Lyapunov stability analysis that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded. In addition, the system tracking performance regarding transient and steady-state behaviors is guaranteed effectively with input saturation via the designed control approach. Finally, numerical simulation results are presented to authenticate and validate the effectiveness of the proposed control scheme.

Keywords