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Discretization of non-linear controls with application to robust, sliding-mode-based control systems

机译:非线性控制的离散化及其在鲁棒,基于滑模的控制系统中的应用

摘要

This thesis deals with sampled-data implementations of continuous-time, non-linear control systems. The basis for the analysis is a static, continuous-time feedback law for non-linear, affine systems with bounded input gain. The sampled-data implementation is obtained from the discretization of the control via a sample-and-hold-process. With the incorporation of the aspect of robustness, a theoretical framework is created which supersedes previous work concentrating on stability. Bounding constraints for the closed-loop differential system allow uncertainty and disturbances to be considered. Other assumptions for the continuous-time control are Lipschitz continuity, exponential decay outside a compact set and existence of a Lyapunov function. The important parameter for the discretization analysis is the sampling time; fast sampling implies robust stability. The controller sampling residual, the difference between the discretized and the original control, is of key interest within a Lyapunov-type stability analysis; suitable norms, such as the Euler norm, are chosen to find upper bounds for the sampling residual. The generalization of a result from linear to non-linear sampled-data control permits the application of the Lp-norm. The theoretical framework is also suitable for dynamic control systems and the investigation of computational delays.;The analysis approaches are demonstrated for two different robust control. strategies .based on sliding-mode approaches. A state-feedback sliding-mode-based control extends ideas for smoothing discontinuous sliding-mode control components by introducing a cone-shaped sliding-mode layer. A non-smooth Lyapunov function is used to prove stability of the discretized control. An observer-based tracking control improves a previous control scheme by considering a class of non-minimum phase and relative-degree-zero plants.;Simulation and numerical fast-sampling analysis results are provided for all developed discretization and sliding-mode-based control techniques in application to non-trivial examples. The simulation of a highly non-linear, large-scale chemical plant for benzene production with non-minimum phase and relative-degree-zero characteristics proves the effectiveness of sliding-mode output control.
机译:本文涉及连续时间非线性控制系统的采样数据实现。分析的基础是具有有限输入增益的非线性仿射系统的静态连续时间反馈定律。采样数据实现是通过采样保持过程从控件的离散化获得的。通过结合健壮性方面,创建了一个理论框架,该框架取代了以前专注于稳定性的工作。闭环微分系统的边界约束允许考虑不确定性和干扰。连续时间控制的其他假设包括Lipschitz连续性,紧集外的指数衰减和Lyapunov函数的存在。离散化分析的重要参数是采样时间。快速采样意味着鲁棒的稳定性。在Lyapunov型稳定性分析中,控制器采样残差(离散化控制和原始控制之间的差异)是关键问题。选择合适的范数,例如欧拉范数,以找到采样残差的上限。从线性采样数据控制到非线性采样数据控制的结果的一般化允许Lp范数的应用。该理论框架也适用于动态控制系统和计算时延的研究。演示了两种不同鲁棒控制的分析方法。基于滑模方法的策略。基于状态反馈的滑模控制通过引入圆锥形滑模层扩展了用于平滑不连续滑模控制组件的思想。非光滑Lyapunov函数用于证明离散控制的稳定性。基于观察者的跟踪控制通过考虑一类非最小相位和相对零度植物改进了先前的控制方案;为所有已开发的离散化和基于滑模的控制提供了仿真和数值快速采样分析结果技术应用于非平凡的例子。对具有最小相位和相对零度特性的苯生产的高度非线性大型化工厂的仿真证明了滑模输出控制的有效性。

著录项

  • 作者

    Herrmann, Guido.;

  • 作者单位
  • 年度 2000
  • 总页数
  • 原文格式 PDF
  • 正文语种 {"code":"en","name":"English","id":9}
  • 中图分类

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