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首页> 外文期刊>Control Theory & Applications, IET >Intelligent double integral sliding-mode control for five-degree-of-freedom active magnetic bearing system
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Intelligent double integral sliding-mode control for five-degree-of-freedom active magnetic bearing system

机译：五自由度主动磁悬浮轴承系统的智能双积分滑模控制

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摘要

This study presents a decentralised intelligent double integral sliding-mode control (IDISMC) system, which consists of five IDISMCs, to regulate and stabilise a fully suspended five-degree-of-freedom (DOF) active magnetic bearing (AMB) system. The system structure and drive system with differential driving mode (DDM) are introduced first. Then, the decoupled dynamic model of the five-DOF AMB is analysed for the design of the decentralised control. Moreover, a decentralised integral sliding-mode control (ISMC) system is designed based on the decoupled dynamic model to control the five-DOF AMB considering the existences of the uncertainties. Furthermore, since the control characteristics of the five-DOF AMB are highly non-linear and time varying, the decentralised IDISMC system is proposed to further improve the control performance of the five-DOF AMB. In each IDISMC, the adopted double integral sliding surface reinforces the control law with the integral (I) control feature. In addition, the control gains of the IDISMC can be adjusted on-line and the system uncertainty can also be observed simultaneously by using of a modified proportional-integral-derivative neural network (MPIDNN) observer. Thus, the proposed IDISMC combines the merits of the ISMC, adaptive control and neural network (NN). Finally, the experimental results illustrate the validities of the proposed control systems using various operating conditions.
机译：这项研究提出了一种分散式智能双积分滑模控制（IDISMC）系统，该系统由五个IDISMC组成，用于调节和稳定完全悬浮的五自由度（DOF）主动磁轴承（AMB）系统。首先介绍了差分驱动模式（DDM）的系统结构和驱动系统。然后，分析了五自由度AMB的解耦动力学模型，以进行分散控制的设计。此外，基于解耦动力学模型，设计了一种分散积分滑模控制（ISMC）系统，以考虑不确定性的存在来控制五自由度AMB。此外，由于五自由度AMB的控制特性是高度非线性且随时间变化的，因此提出了分散式IDISMC系统以进一步改善五自由度AMB的控制性能。在每个IDISMC中，采用的双整体式滑动面通过整体（I）控制功能增强了控制规律。此外，IDISMC的控制增益可以在线调整，并且还可以使用改进的比例积分微分神经网络（MPIDNN）观察器同时观察系统不确定性。因此，提出的IDISMC结合了ISMC，自适应控制和神经网络（NN）的优点。最后，实验结果说明了在各种工况下提出的控制系统的有效性。

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