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Robust Adaptive Neural Prescribed Performance Control for MDF Continuous Hot Pressing System With Input Saturation
Author(s) -
Liangkuan Zhu,
Yugang Zhou,
Yaqiu Liu
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2800778
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
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.

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