Research On Remaining Useful Life Prediction And Life Extension Control Method Of Uncertain Feedback Control System

Driven by the requirements of high safety,reliability and maintainability of complex systems,with the rapid development of new technologies,the academia and industry pay more and more attention to the Prediction and Health Management(PHM)of feedback control systems.For the feedback control system with time limit constraint in engineering practice,how to accurately predict the Remaining Useful Life(RUL)based on the operation state information under the multi-source uncertain factors such as noise,interference and time-varying;and how to take reasonable self maintenance strategy to effectively extend the system life when the system RUL does not meet the time limit requirements,the research and solution of such problems undoubtedly has important significance to improve the security,availability and economy of complex systems,The main work of this thesis includes:1)The framework of life prediction and life extension control for uncertain feedback control system is constructed.Based on the classical structure of feedback control system,this framework introduces two modules,PHM module and DMC based life extension control module.The PHM module aims to predict the RUL of feedback control system in real time under actuator implicit degradation,and the DMC module aims to balance the relationship between system performance and durability by adjusting and optimizing the diagonal elements of error weight matrix Q and control weight matrix R in DMC when the system RUL can not meet the time constraint,so as to ensure that the system life can meet the time limit requirements.2)Aiming at the nonlinear and nonmonotonic characteristics of actuator degradation in the feedback system,and considering the measurement error of the degradation,the nonlinear Wiener model of the actuator degradation process is established,and the implicit degradation of the actuat or and the unknown parameters of the model are obtained by using Kalman filtering and maximum likelihood estimation,respectively.Next,according to the influence of actuator degradation on the steady-state performance of the system,the failure threshold of the system is determined,and the probability density function of the RUL of the system is obtained when the actuator degradation first reaches the definition of the system failure threshold,thus the real-time prediction of the RUL of the system is realized.Then,when the RUL of the system can not meet the time constraint,the adjustment of Q and R elements in DMC is qualitatively associated with the degradation amount,and a DMC segmented life extension strategy is used to delay the degradation of th e actuator,so as to extend the remaining life of the system.3)Considering that actuator degradation in feedback control system is affected by external impact,combined with the consideration of 2),firstly,Wiener + Poisson composite model of actuator degradation process is established,and Kalman filter and Expectation-Maximization(EM)algorithm are used to estimate the implicit degradation amount of actuator and unknown parameters of composite model respectively;Next,the probability density function of RUL under the actuator degradation model is derived to realize the real-time life prediction of the feedback system;Then,when the RUL of the system can not meet the time limit requirement,the adjustment of Q and R elements i n DMC is quantitatively associated with the degradation amount,and a DMC adaptive life extension strateg y is used to ensure that the RUL of the system can meet the time limit constraint.4)Aiming at the problem of time-varying uncertainty and degradation data missing in the process of actuator degradation in feedback control system,combined with the consideration of 3),Firstly,under the multi-source uncertainty such as actuator degradation time-varying and degradation measurement error,a Wiener +Poisson composite model is established,and then Kalman filter and EM algorithm are used to estimate and update the implicit degradation and model parameters in real time.When the RUL of the feedback system can not meet the time constraint,the DMC adaptive life extension strategy is used to extend the system life more effectively under the dual adaptation of RUL and DMC.5)For the above different solutions,this paper selects the double tank level feedback control system as the simulation object,establishes the above models respectively for the degradation process of the internal water pump,realizes the real-time life prediction of the tank level system,and ensures that the system RUL meets the time constraints based on the above DMC different life extensi on strategies.Simulation results show that more accurate actuator degradation model can get more accurate system life prediction resul ts;Compared with the existing Linear Quadratic Regulator(LQR)method,the proposed DMC life extension strategy has bett er life extension effect and robustness,and the quantitative correlation DMC adaptive strategy has better life extension effect than the qualitative one.