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压电作动器的多目标互补鲁棒控制方法研究OA

Research on multi-objective complementary robust control of piezoelectric actuators

中文摘要英文摘要

针对存在模型不确定性、外界干扰和测量噪声下的压电作动器(PEA)高精度跟踪控制问题,本文提出多目标互补鲁棒控制方法.首先,建立基于Hammerstein模型结构的率相关迟滞非线性模型,其中系统的静态迟滞非线性环节采用Prandtl-Ishlinskii(PI)模型描述,动态线性环节则由改进的相关性辨识法得到.然后,在此模型基础上,提出用多目标互补鲁棒控制方法来实现压电作动器的高精度跟踪控制,该控制器应用PID控制理念实现闭环系统的最优性能,并采用鲁棒控制策略达到闭环系统的鲁棒稳定,同时融合了 Youla参数化的思想解决系统最优性能与鲁棒性之间的矛盾.最后,通过实验验证系统的跟踪精度及抗干扰能力,证明了本文所提出方法的有效性.

To address the challenge of achieving high-precision tracking control for piezoelectric actuators(PEAs)in the presence of model uncertainty,external interference,and measurement noise,a novel multi-objective complementary robust control method is proposed in this paper.First,a rate-dependent hysteresis nonlinear model,structured upon the Hammer-stein model,is formulated.This model represents the static hysteresis nonlinear component using the Prandtl-Ishlinskii(PI)model,while the dynamic linear component is characterized by an enhanced correlation identification method.Then,a multi-objective complementary robust control method is employed to achieve the precise tracking control of the piezo-electric actuator.This approach integrates PID control principles to optimize the closed-loop system's performance,in-corporates robust control strategies to ensure the stability of the closed-loop system,and utilizes Youla parameterization to address the conflict between the system's optimal performance and robustness.Finally,the system's tracking accuracy and anti-interference capabilities are verified through experiments,providing empirical evidence for the effectiveness of the proposed methodology in this paper.

陈辉;齐苗苗;刘佳彬;连峰;韩崇昭

兰州理工大学电气工程与信息工程学院,甘肃兰州 730050兰州理工大学电气工程与信息工程学院,甘肃兰州 730050兰州理工大学电气工程与信息工程学院,甘肃兰州 730050西安交通大学自动化科学与工程学院,陕西西安 710049西安交通大学自动化科学与工程学院,陕西西安 710049

压电作动器鲁棒控制相关性辨识Youla参数化卡尔曼滤波多目标互补控制

piezoelectric actuatorsrobust controlrelevance recognitionYoula parameterizationKalmen filtermulti-objective complementary control

《控制理论与应用》 2026 (2)

227-238,12

国家自然科学基金项目(62363023,62163023,61873116,62366031),甘肃省基础研究创新群体项目(25JRRA058),中央引导地方科技发展资金项目(25ZYJA040),甘肃省重点人才项目(2024RCXM86),甘肃省军民融合发展专项资金项目资助.Supported by the National Natural Science Foundation of China(62363023,62163023,61873116,62366031),the Gansu Provincial Basic Research Innovation Group of China(25JRRA058),the Central Government's Funds for Guiding Local Science and Technology Development of China(25ZY-JA040),the Gansu Provincial Key Talent Project of China(2024RCXM86)and the Gansu Provincial Special Fund for Military-Civilian Integration Development of China.

10.7641/CTA.2024.30532

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