A modeling framework for deteriorating control system and predictive maintenance of actuators

Abstract Actuators play a central role in industrial automation systems. They are costly, and therefore studying their dependability needs all attention. Usually, an actuator is inserted in a feedback control system, and its mission is to implement a control action delivered by a controller. In this paper, a monotonic actuator deterioration is considered and it is assumed that a relationship exists between the control action and the physical actuator׳s deterioration. A modeling framework is proposed including a non-decreasing stochastic degradation process driving the inability for an actuator to fully implement its role. The prognosis of the actuator׳s residual useful lifetime is derived and used to update the controller׳s setting. The controller reconfiguration completes the maintenance corrective and preventive actions. This new action is suggested as an alternative for maintenance strategy.

[1]  Youmin Zhang,et al.  Bibliographical review on reconfigurable fault-tolerant control systems , 2003, Annu. Rev. Control..

[2]  Alejandro D. Domínguez-García,et al.  An integrated methodology for the dynamic performance and reliability evaluation of fault-tolerant systems , 2008, Reliab. Eng. Syst. Saf..

[3]  Shengkui Zeng,et al.  Design optimization considering performance and reliability , 2009, 2009 Annual Reliability and Maintainability Symposium.

[4]  Hans Zwart,et al.  State Space Representation , 2012 .

[5]  Tor Arne Johansen,et al.  Control allocation - A survey , 2013, Autom..

[6]  Meng Joo Er,et al.  Bearing Condition Prediction Using Enhanced Online Learning Fuzzy Neural Networks , 2013 .

[7]  Youmin Zhang,et al.  Design of a fault tolerant control system incorporating reliability analysis and dynamic behaviour constraints , 2011, Int. J. Syst. Sci..

[8]  John Vian,et al.  Stochastic Optimal Control of a Servo Motor with a Lifetime Constraint , 2006, Proceedings of the 45th IEEE Conference on Decision and Control.

[9]  Zhigang Tian,et al.  A framework for predicting the remaining useful life of a single unit under time-varying operating conditions , 2013 .

[10]  François Guillet,et al.  A New Bearing Fault Detection Method in Induction Machines Based on Instantaneous Power Factor , 2008, IEEE Transactions on Industrial Electronics.

[11]  Andrew Y. C. Nee,et al.  Re-engineering Manufacturing for Sustainability , 2013 .

[12]  Philippe Weber,et al.  Control design for over-actuated systems based on reliability indicators , 2010 .

[13]  A.H. Bonnett Cause and analysis of anti-friction bearing failures in AC induction motors , 1993, Conference Record of 1993 Annual Pulp and Paper Industry Technical Conference.

[14]  Dragan Banjevic,et al.  Remaining useful life in theory and practice , 2009 .

[15]  Takashi Yoneyama,et al.  Model Predictive Control using Prognosis and Health Monitoring of actuators , 2010, 2010 IEEE International Symposium on Industrial Electronics.

[16]  H.A. Toliyat,et al.  Condition Monitoring and Fault Diagnosis of Electrical Motors—A Review , 2005, IEEE Transactions on Energy Conversion.

[17]  Antoine Grall,et al.  MAINTENANCE POLICY FOR A CONTINUOUSLY MONITORED DETERIORATING SYSTEM , 2003 .

[18]  Simon French,et al.  Encyclopedia of quantitative risk analysis and assessment , 2008 .

[19]  Shu-Hsing Chung,et al.  Analyzing the effects of family-based scheduling rule on reducing capacity loss of single machine with uncertain job arrivals , 2012, Expert Syst. Appl..

[20]  Mitra Fouladirad,et al.  Condition-based inspection/replacement policies for non-monotone deteriorating systems with environmental covariates , 2010, Reliab. Eng. Syst. Saf..

[21]  L.U. Gokdere,et al.  Lifetime control of electromechanical actuators , 2005, 2005 IEEE Aerospace Conference.

[22]  C. Bérenguer,et al.  On the Use of Time-Limited Information for Maintenance Decision Support: A Predictive Approach under Maintenance Constraints , 2013 .

[23]  Philippe Weber,et al.  Reconfigurable control design with integration of a reference governor and reliability indicators , 2012, Int. J. Appl. Math. Comput. Sci..

[24]  D. Theilliol,et al.  Actuator fault tolerant controller synthesis based on second order information , 2007, 2007 European Control Conference (ECC).

[25]  Guang Meng,et al.  A predictive maintenance scheduling framework utilizing residual life prediction information , 2013 .

[26]  Jan M. van Noortwijk,et al.  A survey of the application of gamma processes in maintenance , 2009, Reliab. Eng. Syst. Saf..

[27]  L.U. Gokdere,et al.  Adaptive control of actuator lifetime , 2006, 2006 IEEE Aerospace Conference.

[28]  R. J. Richards Solving problems in control , 1993 .

[29]  Ming Jian Zuo,et al.  An integrated framework for online diagnostic and prognostic health monitoring using a multistate deterioration process , 2014, Reliab. Eng. Syst. Saf..

[30]  Antoine Grall,et al.  A deterioration model for feedback control systems with random environment , 2013 .

[31]  Antoine Grall,et al.  Continuous-time predictive-maintenance scheduling for a deteriorating system , 2002, IEEE Trans. Reliab..

[32]  Frank L. Lewis,et al.  Aircraft Control and Simulation , 1992 .

[33]  J. Jiang,et al.  Reliable State Feedback Control System Design Against Actuator Failures , 1998, Autom..

[34]  Mitra Fouladirad,et al.  Computation of remaining useful life on a physic-based model and impact of a prognosis on the maintenance process , 2013 .

[35]  Dustin G. Mixon,et al.  Availability of periodically inspected systems with Markovian wear and shocks , 2006, Journal of Applied Probability.

[36]  Antonio Visioli,et al.  State–space representation , 2020, Digital Control Engineering.

[37]  M. Sami Fadali Chapter 7 – State–Space Representation , 2013 .