摘要
To deal with fault detection and diagnosis with incomplete model for dead reckoning system of mobile robot,an integrative framework of particle filter detection and fuzzy logic diagnosis was devised.Firstly,an adaptive fault space is designed for recognizing both known faults and unknown faults,in corresponding modes of modeled and model-free.Secondly,the particle filter is utilized to diagnose the modeled faults and detect model-free fault according to the low particle weight and reliability.Especially,the proposed fuzzy logic diagnosis can further analyze model-free modes and identify some soft faults in unknown fault space.The MORCS-1 experimental results show that the fuzzy diagnosis particle filter(FDPF) combinational framework improves fault detection and identification completeness.Specifically speaking,FDPF is feasible to diagnose the modeled faults in known space.Furthermore,the types of model-free soft faults can also be further identified and diagnosed in unknown fault space.
To deal with fault detection and diagnosis with incomplete model for dead reckoning system of mobile robot, an integrative framework of particle filter detection and fuzzy logic diagnosis was devised. Firstly, an adaptive fault space is designed for recognizing both known faults and unknown faults, in corresponding modes of modeled and model-free. Secondly, the particle filter is utilized to diagnose the modeled faults and detect model-free fault according to the low particle weight and reliability. Especially, the proposed fuzzy logic diagnosis can further analyze model-free modes and identify some soft faults in unknown fault space. The MORCS-1 experimental results show that the fuzzy diagnosis particle filter （FDPF） combinational framework improves fault detection and identification completeness. Specifically speaking, FDPF is feasible to diagnose the modeled faults in known space. Furthermore, the types of model-free soft faults can also be further identified and diagnosed in unknown fault space.
基金
Project(90820302) supported by the National Natural Science Foundation of China
Project(20110491272) supported by China Postdoctoral Science Foundation of China
Project(2012QNZT060) supported by the Fundamental Research Fund for the Central Universities of China
Project(11B070) supported by the Science Research Foundation of Education Bureau of Hunan Province,China
Project(2010-2012) supported by the Postdoctoral Science Foundation of Central South University,China
