具有迟滞特性的作动器建模及逆补偿控制

发布时间：2018-04-02 20:59

本文选题：迟滞非线性　切入点：率相关性　出处：《西南交通大学》2017年硕士论文

【摘要】：作为典型的智能结构,压电作动器和超磁致作动器获得了广泛应用。但是作动器存在复杂的率相关迟滞非线性,会造成系统精度超差,易产生振荡,甚至闭环系统不稳定等问题。如何对智能结构进行建模和控制,具有重要的理论研究意义和工程应用价值。本文以压电作动器和超磁致作动器为控制对象,深入研究率相关迟滞非线性系统的逆补偿控制理论与方法,旨在消除率相关迟滞非线性对控制精度的影响,分别实现压电作动器和超磁致作动器的实时跟踪控制。文章从迟滞非线性系统建模、逆补偿控制策略设计、实验验证三个层次展开,主要研究内容如下:采用Hammerstein模型思想分别建立压电作动器和超磁致作动器的迟滞模型。采用BP神经网络和ARX模型分别表征作动器的迟滞非线性和率相关性。采用扩展空间输入法,以神经网络结合play算子构建的基本迟滞算子,来克服作动器的多值映射性。建模结果表明,无论是压电作动器还是超磁致作动器,所设计的模型都能描述其迟滞非线性,而且具有易于辨识、频率泛化能力强等优点。设计了前馈反馈复合控制策略对压电作动器和超磁致作动器进行跟踪控制。采用作动器的Hammerstein逆模型构建前馈控制器,分别设计了 PID控制、基于单神经元PID控制、模糊PD控制三种反馈控制器。搭建了基于dSPACE半实物仿真平台的作动器实时跟踪控制实验系统,介绍了实验流程和S-Function的编写方法。对压电作动器和超磁致作动器,分别设计了实时跟踪控制实验。对实验结果进行了分析和比较。跟踪结果表明,对压电作动器和超磁致作动器,所设计的复合控制策略都能有效跟踪,能够满足工程和研究需要。
[Abstract]:As a typical intelligent structure, piezoelectric actuators and giant magnetic actuators have been widely used.However, the actuator has complex rate dependent hysteresis nonlinearity, which will lead to the system accuracy is too poor, easy to produce oscillations, even closed-loop system instability and so on.How to model and control intelligent structures has important theoretical significance and engineering application value.Taking piezoelectric actuator and giant magnetic actuator as control objects, the inverse compensation control theory and method for rate-dependent hysteresis nonlinear systems are studied in this paper, in order to eliminate the influence of rate-dependent hysteresis nonlinearity on control accuracy.The real-time tracking control of piezoelectric actuator and giant magnetic actuator is realized respectively.In this paper, three levels of hysteresis nonlinear system modeling, inverse compensation control strategy design and experimental verification are developed. The main research contents are as follows: the hysteresis models of piezoelectric actuator and giant magnetic actuator are established by using Hammerstein model.The hysteresis nonlinearity and rate correlation of actuator are characterized by BP neural network and ARX model, respectively.The extended space input method and the basic hysteresis operator constructed by neural network combined with play operator are used to overcome the multi-valued mapping of actuators.The modeling results show that both the piezoelectric actuator and the giant magnetic actuator can describe the hysteresis nonlinearity and have the advantages of easy identification and strong frequency generalization.A feedforward and feedback compound control strategy is designed to track and control piezoelectric actuators and giant magnetic actuators.The feedforward controller is constructed by using the Hammerstein inverse model of actuator. Three kinds of feedback controllers are designed: PID control, single neuron PID control and fuzzy PD control.A real-time tracking control experiment system of actuators based on dSPACE hardware-in-the-loop simulation platform is built. The experimental flow and the programming method of S-Function are introduced.Real-time tracking control experiments are designed for piezoelectric actuators and giant magnetic actuators.The experimental results are analyzed and compared.The tracking results show that both the piezoelectric actuator and the Giant Magneto-Actuator can be tracked effectively and can meet the needs of engineering and research.
【学位授予单位】：西南交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP273

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