Abstract

Fault tolerance is increasingly important in industrial robots. The ability to detect and tolerate failures allows robots to effectively cope with internal failures and continue performing designated tasks without the need for immediate human intervention. This paper presents new fault detection algorithms which detect failures in robot components using sliding-mode observers. An intelligent fault tolerance framework is proposed in which the detection algorithms work to detect and tolerate sensor or motor failures in a robot system. The nonlinear observer is designed to provide the estimation of unmeasurable state and modelling uncertainty, which are used to construct fault estimation algorithm. The effectiveness of the control and the fault tolerance strategy is analyzed in simulation.

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