论文标题
使用DREM进行开关未知参数的一类系统的自适应观察者
Adaptive Observer for a Class of Systems with Switched Unknown Parameters Using DREM
论文作者
论文摘要
在本说明中，我们为具有切换未知参数的一类非线性系统开发自适应观察者，以同时估计状态和参数。主要挑战在于如何消除由切换参数估计引起的零输入响应的干扰效应。这些响应取决于开关Instants（SASI）的未知状态，并构成了参数估计的加性干扰，该估计阻碍了参数收敛至零。我们的解决方案是将零输入响应视为激发而不是干扰。首先使用SASI增强系统参数，然后使用\ textIt {Dynamic Recression扩展和混合}（DREM）技术来开发一个估计器，从而实现这一点。由于其元素和元素参数适应的属性，系统参数估计与SASI分离。结果，系统状态和参数的估计误差会渐近地收敛到零。此外，在存在干扰和噪声的情况下，保证了所提出的自适应观察者的鲁棒性。一个数值示例验证了所提出的方法的有效性。
In this note, we develop an adaptive observer for a class of nonlinear systems with switched unknown parameters to estimate the states and parameters simultaneously. The main challenge lies in how to eliminate the disturbance effect of zero-input responses caused by the switching on the parameter estimation. These responses depend on the unknown states at switching instants (SASI) and constitute an additive disturbance to the parameter estimation, which obstructs parameter convergence to zero. Our solution is to treat the zero-input responses as excitations instead of disturbances. This is realized by first augmenting the system parameter with the SASI and then developing an estimator for the augmented parameter using the \textit{dynamic regression extension and mixing} (DREM) technique. Thanks to its property of element-wise parameter adaptation, the system parameter estimation is decoupled from the SASI. As a result, the estimation errors of system states and parameters converge to zero asymptotically. Furthermore, the robustness of the proposed adaptive observer is guaranteed in the presence of disturbances and noise. A numerical example validates the effectiveness of the proposed approach.
