An on-line expert system-based fault-tolerant control system

Abstract

Fault-tolerant control systems have been studied very actively during recent years. Software and hardware redundancy techniques are the most common methods used to solve the problems. In recent years, expert systems or artificial intelligence have been used successfully in fault diagnosis of the dynamic systems and their suitability for fault-tolerant control problems has also been demonstrated. In this paper an on-tine expert system-based fault-tolerant control system (ESFTC) is considered which allows reconfiguration of the controller in feedback process systems during sensor or actuator failures or misoperudon. It forms an on-line expert system, which consists of an analytical problem solution, a process knowledge base, a knowledge acquisition part and an inference mechanism. The analytical problem solution is based on process coefficient changes, which are symptoms of process faults. A controller is reconfigured based on the symptoms. The process knowledge base comprises analytical knowledge in the form of process performances and heuristic knowledge in the form of fault trees and fault statistics. In the phase of knowledge acquisition the process specific knowledge, like theoretical process models, the abnormal behavior, failures and misoperation, is compiled The inference mechanism performs the fault-tolerant controller, based on the observable symptoms, controller trees, fault probabilities and process history. Case study experiments with the Yeast Fermentation Process Control System show the performance of the fault-tolerant controller.