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From Deterioration Modeling to Remaining Useful Life Control

其他書名	A Comprehensive Framework for Post-prognosis Decision-making Applied to Friction Drive Systems
出版	2018
URL	http://books.google.com.hk/books?id=EtIe0AEACAAJ&hl=&source=gbs_api

註釋Remaining Useful Lifetime (RUL) can be simply defined as a prediction of the remaining time that a system is able to perform its intended function, from the current time to the final failure. This predicted time mostly depends on the state of deterioration of the system components and their expected future operating conditions. Thus, the RUL prediction is an uncertain process and its control is not trivial task.In general, the purpose for predicting the RUL is to influence decision-making for the system. In this dissertation a comprehensive framework for controlling the RUL is presented. Model uncertainties as well as system disturbances have been considered into the proposed framework. Issues as uncertainty treatment and inclusion of RUL objectives in the control strategy are studied from the modeling until a final global control architecture. It is shown that the RUL can be predicted from a suitable estimation of the deterioration, and from hypothesis on the future operation conditions. Friction drive systems are used for illustrating the usefulness of the aforementioned global architecture. For this kind of system, the friction is the source of motion and at the same time the source of deterioration. This double characteristic of friction is a motivation for controlling automatically the deterioration of the system by keeping a trade-off, between motion requirements and desired RUL values. In this thesis, a new control-oriented model for friction drive systems, which includes a dynamical model of the deterioration is proposed. The amount of deterioration has been considered as a function of the dissipated energy, at the contact surface, during the mechanical power transmission. An approach to estimate the current deterioration condition of a friction drive system is proposed. The approach is based on an Extended Kalman Filter (EKF) which uses an augmented model including the mechanical dynamical system and the deterioration dynamics. At every time instant, the EKF also provides intervals which surely includes the actual deterioration value which a given probability. A new architecture for controlling the RUL is proposed, which includes: a deterioration condition monitoring system (for instance the proposed EKF), a system operation condition estimator, a RUL controller system, and a RUL actuation principle. The operation condition estimator is based on the assumption that it is possible quantify certain characteristics of the motion requirements, for instance the duty cycle of motor torques. The RUL controller uses a cost function that weights the motion requirements and the desired RUL values to modify a varying-parameter filter, used here as the RUL-actuating-principle. The RUL-actuating-principle is based on a modification of the demanded torques, coming from a possible motion controller system. Preliminary results show that it is possible to control de RUL according to the proposed theoretical framework.