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Model-Free Adaptive Control of Direct Drive Servo Valve of Electromagnetic Linear Actuator

机译：电磁线性执行器直驱伺服阀的无模型自适应控制

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摘要

An electromagnetic linear actuator (EMLA) has a promising application in direct motion control. However, ELMA will inevitably inherit uncertainties in the face of load changes, system parameter perturbation, and inherent system nonlinearities, all of which constitute disturbances adversely affecting the precision and adaptability of the control system. A model-free adaptive control (MFAC) strategy based on full form dynamic linearization (FFDL) was proposed to reduce the sensitivity of the control system to the disturbances. An adaptive control of direct drive servo valve was achieved based on the online interaction of characteristic parameters and control algorithms. The feasibility and precision of the proposed algorithm were verified through simulation and experimental results. The results show that the proposed algorithm could achieve adaptive adjustment of the servo valve response at different openings of 0-3 mm without changing control parameters, with the response time controlled within 10ms and steady state error less than 0.04mm. Furthermore, the proposed algorithm had better robustness and capacity of resisting disturbance.
机译：电磁线性执行器（EMLA）在直接运动控制中具有广阔的应用前景。但是，面对负载变化，系统参数扰动和固有的系统非线性，ELMA不可避免地会继承不确定性，所有这些因素都会构成干扰，对控制系统的精度和适应性产生不利影响。为了降低控制系统对干扰的敏感度，提出了一种基于完整动态线性化（FFDL）的无模型自适应控制（MFAC）策略。基于特征参数和控制算法的在线交互，实现了直驱伺服阀的自适应控制。通过仿真和实验结果验证了该算法的可行性和精度。结果表明，该算法在不改变控制参数的情况下，可以在0〜3mm的不同开度上实现伺服阀响应的自适应调节，响应时间控制在10ms以内，稳态误差小于0.04mm。此外，该算法具有较好的鲁棒性和抗干扰能力。

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  • 来源
    《Mathematical Problems in Engineering》 |2018年第14期|7105872.1-7105872.11|共11页
  • 作者

    Zhu Jianhui; Dai Jianguo; Wang Cheng;

  • 作者单位

    Huaiyin Inst Technol, Fac Transportat Engn, Huaian 223003, Peoples R China|Nanjing Univ Sci & Technol, Sch Mech Engn, Nanjing 210094, Jiangsu, Peoples R China;

    Huaiyin Inst Technol, Fac Transportat Engn, Huaian 223003, Peoples R China;

    Huaiyin Inst Technol, Fac Transportat Engn, Huaian 223003, Peoples R China;

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