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Design and Analysis of Model Based Nonlinear and Multi-Spectral Controllers with Focus on Motion Control of Continuous Smart Structures.

机译：基于模型的非线性和多谱控制器的设计和分析，其重点是连续智能结构的运动控制。

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摘要

Smart structures are currently utilized in many applications from precision positioning control of large space structures to active vibration control of machine components. Despite their relative easiness in controlling, positioning accuracy and longevity can be compromised by the hysteresis. In addition, current active control algorithms are limited predominantly to the control of a single or multiple sinusoidal waves and these are incapable of addressing more complicated multi-spectral signals such as modulated signatures. This dissertation introduces model-based and nonlinear control techniques aimed at the reduction of hysteretic effect and for their application to active motion control.;A nonlinear energy-based hysteresis model is developed for a piezoelectric stack actuator and model predictive sliding mode control is applied to force the system state to reach a sliding surface in an optimal manner and to accurately track the reference signal. This method is employed on pre-stressed curved unimorph actuators (modeled by a second order differential equation) with an additional time delay term to describe the hysteretic effect. Simulations and experiments are conducted to validate this approach, and the results highlight significantly improved hysteresis reduction in the displacement control mode. Also, it has been verified that the performance of the novel control methods is not much affected by the accuracy of actuator model.;Next, enhanced adaptive filtering algorithms are developed with application to active vibration control. A feedback loop with the model predictive sliding mode control is introduced in the adaptive filtering system. The goal of this study is to manage multi-spectral signals while achieving smooth and effective convergence, self-adaptability, and stability. The performance for new adaptive filtering algorithms is validated numerically and experimentally for different signals and other prevailing characteristics. The proposed algorithms are also compared with traditional algorithms for both narrowband and broadband control of signals with complex frequency spectra. The novel technique deals with primary peaks, sidebands, and broadband level simultaneously without a full knowledge of the unwanted signals.
机译：从大空间结构的精确定位控制到机械部件的主动振动控制，智能结构目前在许多应用中得到了利用。尽管它们相对容易控制，但滞后会影响定位精度和寿命。另外，当前的主动控制算法主要限于对单个或多个正弦波的控制，并且它们不能处理更复杂的多光谱信号，例如调制信号。本论文介绍了基于模型的非线性控制技术，旨在减少滞后效应，并将其应用于主动运动控制中。;建立了基于非线性能量的压电滞后模型，并将其应用于模型预测滑模控制。迫使系统状态以最佳方式到达滑动表面并准确跟踪参考信号。此方法用于预应力弯曲单压电晶片执行器（由二阶微分方程建模），并带有附加的时延项来描述滞后效应。进行了仿真和实验以验证这种方法，结果表明，位移控制模式下的磁滞降低明显改善。并且，已经验证了新型控制方法的性能不受致动器模型精度的影响不大。接下来，开发了用于自适应振动控制的增强型自适应滤波算法。在自适应滤波系统中引入了具有模型预测滑模控制的反馈回路。这项研究的目的是管理多光谱信号，同时实现平滑有效的收敛，自适应性和稳定性。新的自适应滤波算法的性能在数字和实验上针对不同信号和其他主要特征进行了验证。还将所提出的算法与传统算法进行比较，以对具有复杂频谱的信号进行窄带和宽带控制。这项新技术可以同时处理主要峰值，边带和宽带电平，而无需完全了解不需要的信号。

著录项

  • 作者

    Kim, Byeongil.;

  • 作者单位

    The Ohio State University.;

  • 授予单位 The Ohio State University.;
  • 学科 Engineering Mechanical.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 224 p.
  • 总页数 224
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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