Data Driven Fault Diagnosis and Fault Tolerant Control: Some Advances and Possible New Directions

This paper presents a selected survey covering the advances of fault diagnosis and fault tolerant control using data driven techniques. A brief summary of the general developments in fault detection and diagnosis for industrial processes is given, which is then followed by discussions on the widely used data driven and knowledge-based techniques. A successful application example is also given, which deals with faults caused by the misplacement of control loop set points and several areas of potential future directions are included in the paper. Key words Fault detection, fault diagnosis, fault tolerant control, data driven techniques Fault detection and diagnosis (FDD) and fault tolerant control (FTC) have been the subject of considerable in-terest in the control research community[1−39]. This is in response to the ever increasing requirements on the reliable operation of control systems, which are, in most cases, sub-ject to a number of faults either in the internal closed loops or from environmental factors. Once system faults have occurred, they can cause unrecoverable losses and result in unacceptable environmental pollution, etc. Occasionally,