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首页> 外文期刊>International Journal of Adaptive Control and Signal Processing >Linear repetitive learning controls for nonlinear systems by Pade approximants
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Linear repetitive learning controls for nonlinear systems by Pade approximants

机译：基于Pade近似的非线性系统的线性重复学习控制

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摘要

We discuss the use of [m,m]-Pade approximants in the implementation of repetitive learning controls solving the output tracking problem (via output error feedback) in the presence of uncertain periodic reference and/or disturbance signals with known common period. The aim is to address the stability issues concerning those approximants when a linear learning controllerdesigned through a detailed stability proof (involving the use of a suitable Lyapunov-like function) and described by a transfer function exhibiting all its poles with negative real partis to be obtained as well as to evaluate the corresponding closed-loop performances: robustness (for instance with respect to additive disturbance noises due to unmodeled sensor dynamics) is consequently achieved with improvements in the output tracking errors appearing as the approximation order m increases. Even though the case of any relative degree may be explicitly addressed, in this paper, for the sake of clarity, we restrict our attention to the learning problem for the class of single-input, single-output, minimum phase, time-invariant systems with known relative degree = 2, uncertain parameters and uncertain output-dependent nonlinearities. Numerical simulation results illustrate the theoretical derivations. Copyright (c) 2014 John Wiley & Sons, Ltd.
机译：我们讨论[m，m] -Pade近似值在重复学习控制的实现中的使用，该学习控制在存在不确定周期参考和/或具有已知公共周期的干扰信号的情况下（通过输出误差反馈）解决输出跟踪问题。目的是解决通过详细的稳定性证明（涉及使用合适的Lyapunov型函数）设计并通过传递函数表示其所有极点具有负实数部分的线性学习控制器而设计的线性学习控制器时与那些近似值有关的稳定性问题。以及评估相应的闭环性能：鲁棒性（例如，由于未建模的传感器动力学而导致的附加干扰噪声）随着近似阶数m的增加而出现的输出跟踪误差得以改善。即使可以明确解决任何相对学位的问题，在本文中，为了清楚起见，我们将注意力集中在单输入，单输出，最小相位，时不变系统的学习问题上已知相对度= 2，不确定参数和不确定输出相关的非线性。数值模拟结果说明了理论推导。版权所有（c）2014 John Wiley＆Sons，Ltd.

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