Fault Tolerance (FT) enables system to continue operating despite in the event of failures. Therefore, FT serves as a backup component or procedure that can immediately play its role to minimize any service lost. FT exists in many forms, where it can either be in the software form or hardware form or both hardware and software form. Fault Tolerance is an umbrella term for fault detection, fault isolation, fault identification and fault solving. To better visualize the fault detection and isolation process, a two wheel robot is used in this study to represent the complex system. The aim of this research is to construct and design a Fault Tolerance algorithm considered to speed up the fault isolation procedure and it might identify multiple fault with the same static fault signature. The Finite State Machine (FSM) model, a wide library of reusable model for the fault tolerant is used in this study to solve the fault in actuator or in the sensor by resetting and adjusting it to the correct position. Using the system sensors or actuators, the technique used is able to recognize the fault from its data. This FSM method is capable to avoid, replace, reset and recover any possible faults occurred in the system, offering an innovative solution to identify and solve a fault immediately.
Keywords: Kalman filter; Artificial Neural Network; Fault tolerant; Fault detection; Fault Isolation