Sensor Fault Diagnosis and Fault Tolerant Control for Automated Guided Forklift

Abstract

For the problem of multiple sensor faults in the automated guided forklift (AGF), an equivalent model with system faults and disturbances is established. To detect multiple sensor faults in the AGF, a sliding mode observer (SMO) is proposed. It introduces a fault estimation algorithm that is designed by the fault residual and the residual is only sensitive to sensor faults which means that the SMO is robust to unknown input disturbances. On the other side, it can also judge the faulty sensor according to the feature vector of different sensors. To judge the type of sensor faults accurately, a mathematical model of sensor fault characteristics is established and it can provide a foundation for choosing appropriate fault-tolerant output compensation measures. Then an active fault-tolerant control method based on state feedback is proposed. It can restore the control system to normal and maintain the stability of the control system. Finally, experiments are given to verify the effectiveness of the proposed fault-tolerant control strategy.