Performance Recovery of Dynamic Feedback-Linearization Methods for Multivariable Nonlinear Systems
Performance Recovery of Dynamic Feedback-Linearization Methods for Multivariable Nonlinear Systems
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DOI：
10.1109/tac.2019.2924176
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发表时间：
2020-04
影响因子：
6.8
通讯作者：
Yuanqing Wu;A. Isidori;Renquan Lu;H. Khalil
中科院分区：
文献类型：
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作者：
Yuanqing Wu;A. Isidori;Renquan Lu;H. Khalil
我们表明，在本文中，如何反馈线性化的多变量可逆非线性系统的经典方法，通过动态扩展和状态反馈，可以robustified。控制器的合成是通过一个递归的过程，在每个阶段，包括在系统状态空间的扩增，使反馈线性化可能的目的，并在一个高增益的扩展观测器的设计，估计的目的，以及由于模型的不确定性的扰动的工厂的状态。其结果是，得到一个闭环系统，对于任何有界的初始条件和任何有界的输入，恢复的性能，将通过经典的反馈线性化技术，通过动态状态反馈。
We show, in this paper, how a classical method for feedback linearization of a multivariable invertible nonlinear system, via dynamic extension and state feedback, can be robustified. The synthesis of the controller is achieved by means of a recursive procedure that, at each stage, consists in the augmentation of the system state space, to the purpose of rendering feedback-linearization possible, and in the design of a high-gain extended observer, to the purpose of estimating the state of the plant as well as the perturbations due to model uncertainties. As a result, a closed-loop system is obtained that, for any bounded set of initial conditions and any bounded input, recovers the performance that would have been obtained by means of the classical technique of feedback linearization via dynamic state feedback.