A model-based fault diagnosis of sensor and actuator of powered wheelchair

This paper describes a method of fault diagnosis of internal sensors and actuators for a wheelchair. We handle hard fault and scale fault of three sensors (two wheel-resolvers and one gyro) and hard fault of two actuators (two wheel motors). The hard fault of the gyro is diagnosed based on mode probability estimated with interacting multi-model estimator. The hard fault of the wheel resolver and motor is diagnosed based on the gyro output as well as the mode probability. The scale fault is diagnosed based on estimating the wheelchair velocity with in-vehicle laser range sensor via a scan matching method. The iterative closest point algorithm is applied for the robust estimate of the wheelchair velocity in usual indoor environments. Experimental results validate the effectiveness of our method.