Adaptive output feedback fault-tolerant control for a class of nonlinear systems based on a sensor fusion mechanism

This paper investigates an output feedback adaptive fault-tolerant tracking control for a class of nonlinear systems with system nonlinearities, sensor failures and external disturbances, in which sensor redundancy is employed to enhance measurement reliability. A sensor fusion mechanism, together with a novel history-based weighted average algorithm is first designed to fuse all sensor outputs. Then, an adaptive controller based on the sensor fusion output, a dynamic gain and a state observer is constructed to handle all the uncertainties caused by system nonlinearities, external disturbances, sensor failures and fusion mechanism. It is shown that by using the proposed scheme, the closed-loop system is stable, the sensor fusion mechanism can eliminate the effects of faulty sensors, and the real tracking error can be driven into a small compact set mainly affected by the fusion error. Experimental results are accomplished to validate the proposed scheme. •An adaptive output feedback tracking scheme with redundant sensors and sensor fusion mechanism.•A novel weighted algorithm is proposed to obtain a continuous and differentiable fusion function.•The weighting functions can regulate their values to eliminate the effects of faulty sensors.•Minority sensors can lose all effectiveness so that the sensor failure patterns are more general.