This paper develops a method for estimating the state of deterioration of a friction drive system and presents its use for predicting and controlling the Remaining Useful Life (RUL) of such a system. The friction drive system is assumed to be affected by endogenous uncertainties and exogenous disturbances. The proposed method is intended for on-line estimation of the contact surface deterioration and it is based on a parameter-varying model that includes both the motion dynamics and the deterioration dynamics of the device. Since, in the presented setting, the control actions on the mechanical system play a role on the non-linear deterioration dynamics, an Extended Kalman Filter is developed for simultaneously estimating both the state of deterioration and its associated estimation error bounds. A numerical example is presented to illustrate the interest of such estimations for RUL prognosis and RUL control. The presented example considers the availability of angular speed measurements and the possibility of re-planning motor torques and/or re-planning desired angular speeds in order to control RUL based on RUL prognosis.

本文开发了一种估计摩擦驱动系统劣化状态的方法，并介绍了该方法在预测和控制此类系统的剩余使用寿命 (RUL) 中的用途。假设摩擦驱动系统受到内生不确定性和外生干扰的影响。所提出的方法旨在用于接触表面退化的在线估计，它基于一个参数变化模型，该模型包括设备的运动动力学和退化动力学。由于在目前的设置中，机械系统上的控制动作对非线性恶化动态起作用，因此开发了扩展卡尔曼滤波器以同时估计恶化状态及其相关的估计误差界限。给出了一个数值例子来说明这种估计对 RUL 预后和 RUL 控制的兴趣。所呈现的示例考虑了角速度测量的可用性以及重新规划电机扭矩和/或重新规划所需角速度以便基于 RUL 预测来控制 RUL 的可能性。