Decentralized Adaptive Control with Fractional Order Elimination of Obsolete Information

J. Tar, J. Bitó, I. Rudas, T. A. Várkonyi
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引用次数: 5

Abstract

In this paper an alternative of Lyapunov's complicated "direct" method, "Robust Fixed Point Transformation (RFPT)" based adaptive controller is applied in decentralized manner for the control of two dynamically coupled, imperfectly and imprecisely modeled mechanical systems. Each subsystem consists of a cart plus a double pendulum provided with a local controller having no information on the existence and the physical state of the second pendulum and on the existence of and dynamic connection to the other cart pendulums system. Instead trying to develop a complete and generally useful system model the RFPT-based solution extracts information only on the present and recent behavior of the controlled system only in the given control situation. Insisting only on the use of the "present experiences" makes the method noise sensitive. To improve the situation the use of "recent experiences" with properly fading obsolete information is a viable solution. For this purpose parametric, discrete numerical approximation of Caputo's fractional order derivatives with "memory properties" are successfully used. It is shown by convincing simulation results that via observing and controlling the state propagation only of the modeled axles the uncorrelated controllers can precisely track their prescribed trajectories.
分数阶消除过时信息的分散自适应控制
本文将基于鲁棒不动点变换(RFPT)的自适应控制器作为Lyapunov复杂“直接”方法的另一种选择,以分散的方式应用于两个动态耦合、不完美和不精确建模的机械系统的控制。每个子系统由一个小车和一个双摆组成,该双摆配有一个本地控制器,该控制器不知道第二个摆的存在和物理状态,也不知道另一个小车摆系统的存在和动态连接。而不是试图开发一个完整的和普遍有用的系统模型,基于rfp的解决方案只提取信息的当前和最近的行为的被控系统只在给定的控制情况。只坚持使用“当前经验”使该方法对噪声敏感。为了改善这种情况,使用“最近的经验”,适当地淡化过时的信息是一个可行的解决方案。为此,成功地使用了具有“记忆性质”的Caputo分数阶导数的参数离散数值近似。仿真结果表明,通过观察和控制被建模轴的状态传播,非相关控制器可以精确地跟踪其指定轨迹。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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