论文标题
消极和沉浸式修饰的梯度估计器：参数估计的控制视角
Passivity and Immersion based-modified gradient estimator: A control perspective in parameter estimation
论文作者
论文摘要
在本文中，提出了一种建设性和系统的策略，具有更明显的自由度，以通过控制角度准确地估算未知参数的准确估算。通过在梯度动力学的最终方程式中添加虚拟控件，扩展了梯度估计器（GE）和内存回归器和扩展方法（MRE）方法。虚拟控制法的解决方案是通过P＆I方法确定的。 P＆I方法基于选择适当的隐式歧管以及适当的被动输出和相关存储功能的生成。这促进了要获得的虚拟控制定律，即参数误差渐近地收敛至零。由于上述想法与P＆I方法和GE相关，因此开发的方法将基于被动性和基于沉浸式的修改梯度估计器（MGE）标记。提出的基于P＆I的修改梯度估计器通过MRE方法扩展。这种修改提供了改进的瞬态响应和快速收敛。基于某些PE和非PE示例，进行了比较分析以显示所提出方法的功效。
In this paper, a constructive and systematic strategy with more apparent degrees of freedom to achieve the accurate estimation of unknown parameters via a control perspective is proposed. By adding a virtual control in the final equation of the gradient dynamics, the Gradient Estimator (GE) and Memory Regressor and Extension (MRE) approaches are extended. The solution of the virtual control law is identified by the P&I approach. The P&I approach is based on the choice of an appropriate implicit manifold and the generation of a suitable passive output and a related storage function. This facilitates the virtual control law being obtained in a way that the parametric error converges asymptotically to zero. Because the above ideas connect with the P&I approach and GE, the developed methodology is labeled the passivity and immersion-based modified gradient estimator (MGE). The proposed P&I-based modified gradient estimator is extended via the MRE approach. This modification provides improved transient response and fast convergence. Based on certain PE and non-PE examples, a comparative analysis is carried out to show the efficacy of the proposed approaches.
