An active fault tolerant control method based on support vector machines

In this study, an active Fault Tolerant Control (FTC) method based on Support Vector Machines (SVM) is presented. The proposed FTC method is not limited to certain faults in the reconfiguration manner and but it also includes a reconfiguration mechanism with direct on-line controller calculation. Here, PID type controller is utilized within the method as a reconfiguration sub-system. The reconfiguration mechanism and the diagnosis unit work independently within the method. Therefore, there is no need for the isolation of faults before tolerating them. In diagnosis and reconfiguration stages of the method, support vector regression machines are used. This FTC technique uses the real-time data generated by the system and it produces the appropriate gains of the controller in an on-line manner. The PID controller coefficients or the gains to be used in the training stage for faulty and non-faulty cases are all obtained by using the Genetic Algorithm optimization approach in an off-line manner. Moreover, it has also been shown that the proposed method can handle multiple and simultaneous occurrences of various types of faults. The performance of the proposed method is tested on a simulation model of two tank level control system for various fault scenarios.