Sensor Fault Diagnosis and Tolerant Control Based on Belief Rule Base for Complex System

This paper develops a new fault diagnosis and tolerant control framework of sensor failure (SFDTC) for complex system such as rockets and missiles. The new framework aims to solve two problems: The lack of data and the multiple uncertainty of knowledge. In the SFDTC framework, two parts exist: The fault diagnosis model and the output reconstruction model. These two parts of the new framework are constructed based on the new developed belief rule base with power set (BRB-PS). The multiple uncertainty of knowledge can be addressed by the local ignorance and global ignorance in the new developed BRB-PS model. Then, the stability of the developed framework is proved by the output error of the BRB-PS model. For complex system, the sensor state is determined by many factors and experts cannot provide accurate knowledge. The multiple uncertain knowledge will reduce the performance of the initial SDFTC framework. Therefore, in the SFDTC framework, to handle the influence of the uncertainty of expert knowledge and improve the framework performance, a new optimization model with two optimization goals is developed to ensure the smallest output uncertainty and the highest accuracy simultaneously. A case study is conducted to illustrate the effectiveness of the developed framework.