论文标题
使用数据驱动模型对机械系统的反馈线性化
Feedback linearisation of mechanical systems using data-driven models
论文作者
论文摘要
线性化非线性机械系统的动力学是一个重要且开放的研究领域。一种常见的方法是反馈线性化，这是一种非线性控制方法，它将非线性系统的输入输出响应转换为等效线性。反馈线性化的主要问题是，它需要系统的准确的第一原理模型，通常很难获得。在本文中，我们设计了一种替代控制方法，该方法利用数据驱动的模型来线性化非线性机械系统的输入输出响应。具体而言，为具有输出非线性的非线性反馈系统开发了基于模型的参考跟踪体系结构。总体方法表明，高度的性能结合了不完美的建模和外推的显着鲁棒性。这些发现是使用在不对称的振荡器上进行的大量合成实验以及使用高精度运动系统的实验原型进行了证明的。
Linearising the dynamics of nonlinear mechanical systems is an important and open research area. A common approach is feedback linearisation, which is a nonlinear control method that transforms the input-output response of a nonlinear system into an equivalent linear one. The main problem with feedback linearisation is that it requires an accurate first-principles model of the system, which are typically hard to obtain. In this paper, we design an alternative control approach that exploits data-driven models to linearise the input-output response of nonlinear mechanical systems. Specifically, a model-based reference tracking architecture is developed for nonlinear feedback systems with output nonlinearities. The overall methodology shows a high degree of performance combined with significant robustness against imperfect modelling and extrapolation. These findings are demonstrated using large set of synthetic experiments conducted on a asymmetric Duffing oscillator and using an experimental prototype of a high-precision motion system.
