首页 | 本学科首页   官方微博 | 高级检索  
     


Integration of multiple model based fault detection and nonlinear model predictive fault‐tolerant control
Authors:Seyed Mohamad Kargar  Karim Salahshoor  Mohamad Javad Yazdanpanah
Abstract:In this paper, we present a new fault‐tolerant control system for a class of nonlinear systems with input constraints. Because of many important factors that stabilize a nonlinear model predictive controller, it can be used as a powerful controller in the event of fault occurrence. So, the reconfigurable controller is designed based on the quasi‐infinite model predictive control (QIMPC) approach as a fault‐tolerant approach. On the other hand, a fault detection and diagnosis (FDD) system is designed based on the multiple model method. The bank of extended Kalman filters (EKFs) is used to detect the predefined actuator fault and estimate the unknown parameters of a fault. When a fault is detected, the proposed FDD information is used to correct the model of the faulty system recursively and reconfigure the controller. Delay on FDD decision may lead to performance degradation or even instability for some systems. The timely proposed FDD approach will preserve stability. Moreover, a framework is presented to ensure stability when a fault occurs. The effectiveness of this method is demonstrated, in comparison with conventional nonlinear model predictive control, by two practical examples. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
Keywords:fault detection and diagnosis  nonlinear model predictive control  extended Kalman filter
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号