Sensor Fault Reconstruction based on Adaptive Sliding Mode Observer for Forklift Fault-Tolerant Control System

Abstract

For the problem of multiple sensor fault detection and reconstruction in the forklift fault-tolerant control system, a sliding mode observer (SMO) with adaptive regulation law is proposed. Based on the three-degree-of-freedom (3-DOF) model of forklift, a linear state equation with output disturbance is designed as its equivalent sensor fault model. The sensor fault is converted into an actuator fault by defining an auxiliary state variable as an output signal filter. Then the SMO-based method of sensor fault detection and reconstruction is given. Without knowing the upper bound of an unknown fault, an adaptive sliding mode observer (ASMO) can also be effective through the adaptive algorithm. Finally, experimental results further verify the effectiveness of the method, and provide a foundation for forklift fault-tolerant control.

A Robust Fault-Tolerant Control for Quadrotor Helicopters against Sensor Faults and External Disturbances

“…In the study by Matus-Vargas et al [10], a fault-tolerant control scheme for a multirotor with altitude sensor faults caused by the ground effect is presented and validated by simulations and experiments. In the study by Zhang and Xiao [11], a sliding mode observer with the adaptive regulation law is proposed for multiple sensor fault detection and reconstruction without knowing the upper bound of the unknown faults. In the study by Tan et al [12], a sliding mode control combined with the RBF neural network is designed to deal with the failures of the sensor and actuator.…”