Discussion on Robust Control Applied to Active Magnetic Bearing Rotor System
Discussion on Robust Control Applied to Active Magnetic Bearing Rotor System
复制标题
主动磁轴承转子系统鲁棒控制的探讨
DOI：
10.5772/17533
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发表时间：
2011
期刊：
影响因子：
--
通讯作者：
A. Piłat
中科院分区：
文献类型：
--
作者：
R. Jastrzebski;A. Smirnov;O. Pyrhonen;A. Piłat
自20世纪80年代以来，出现了一系列关于系统不确定性和鲁棒控制的论文。鲁棒控制依赖于H ∞控制和μ综合，而不是以前喜欢的线性二次高斯控制。然而，高度数学化的技术在没有专用工具的情况下很难应用。这些新方法已经在实际应用中得到了巩固，并出现了一些软件工具箱，如Matlab的鲁棒控制工具箱。本章重点介绍该工具箱在高速转子主动磁轴承悬浮系统中的应用。AMB用于高速旋转机器，如涡轮压缩机，飞轮，机床，分子泵等（Schweitzer & Maslen，2009）。使用主动磁场而不是流体膜、接触滚动元件或滚珠轴承的机械力来支撑转子能够实现高速运行和更低的摩擦损失。AMB的其他主要优点包括无需润滑、使用寿命长、可编程刚度和阻尼、内置监控和诊断以及自动平衡功能。然而，磁悬浮轴承转子系统形成开环不稳定的，多输入多输出（MIMO）耦合的植物与不确定的动态，可以随着时间的推移而变化，并可以在不同的转速显着。在实际系统中，传感器与执行器并不搭配，因此，对象并不总是容易解耦。此外，控制系统面临着过多的外部干扰。磁悬浮轴承技术的主要缺点是难以设计高性能的可靠控制及其实现。对于这样的系统，μ和H ∞控制方法为设计鲁棒控制提供了有用的工具（Moser，1993; Zhou等人，1996年）。采用基于模型的高阶控制器，可以实现对标称对象的无不确定性的高性能、高精度控制。在控制综合的情况下，这是基于不确定的对象模型，有一个折衷的标称性能（时域和频域规格）和鲁棒性之间。建模的不确定性不能太保守，否则获得实际的控制器可能是不可行的（Sawicki & Maslen，2008）。此外，过于复杂的不确定性模型导致控制综合中的数值复杂性增加。用于对照的模型10
Since the 1980s, a stream of papers has appeared on system uncertainties and robust control. The robust control relies on H∞ control and μ synthesis rather than previously favored linear-quadratic Gaussian control. However, highly mathematical techniques have been difficult to apply without dedicated tools. The new methods have been consolidated in the practical applications with the appearance of software toolboxes, such as Robust Control Toolbox from Matlab. This chapter focuses on the application of this toolbox to the active magnetic bearing (AMB) suspension system for high-speed rotors. AMBs are employed in high-speed rotating machines such as turbo compressors, flywheels, machine tools, molecular pumps, and others (Schweitzer & Maslen, 2009). The support of rotors using an active magnetic field instead of mechanical forces of the fluid film, contact rolling element, or ball bearings enables high-speed operation and lower friction losses. Other major advantages of AMBs include no lubrication, long life, programmable stiffness and damping, built-in monitoring and diagnostics, and availability of automatic balancing. However, AMB rotor system forms an open-loop unstable, multiple-input multiple-output (MIMO) coupled plant with uncertain dynamics that can change over time and that can vary significantly at different rotational speeds. In practical systems, the sensors are not collocated with the actuators, and therefore, the plant cannot always be easily decoupled. Additionally, the control systems face a plethora of external disturbances. The major drawback of an AMB technology is a difficulty in designing a high-performance reliable control and its implementation. For such systems, the μ and H∞ control approaches offer useful tools for designing a robust control (Moser, 1993; Zhou et al., 1996). The high-performance and high-precision control for the nominal plant without uncertainties can be realized by using model-based, high-order controllers. In the case of control synthesis, which is based on the uncertain plant model, there is a tradeoff between the nominal performance (timeand frequency-domain specifications) and the robustness. The modeled uncertainties cannot be too conservative or otherwise obtaining practical controllers might be not feasible (Sawicki & Maslen, 2008). Moreover, too complex uncertainty models lead to increased numerical complexity in the control synthesis. The models applied for the control 10