%A Chuan MA,Yancheng LIU,Siyuan LIU,Qinjin ZHANG %T Robust adaptive self-organizing neuro-fuzzy tracking control of UUV with unknown dead-zone nonlinearity %0 Journal Article %D 2019 %J Journal of Shandong University(Engineering Science) %R 10.6040/j.issn.1672-3961.0.2018.385 %P 47-56 %V 49 %N 3 %U {http://gxbwk.njournal.sdu.edu.cn/CN/abstract/article_1826.shtml} %8 2019-06-20 %X

A robust adaptive self-organizing neuro-fuzzy control scheme for trajectory tracking of unmanned underwater vehicle with uncertainties and unknown dead-zone nonlinearity was proposed. The scheme adopted a novel sliding mode reaching law control framework and a self-organizing neuro-fuzzy network approximator to estimate the unknown dynamic and self-adaptive the parameter. The robust controller was employed to provide the finite L2-gain property to cope with reconstruction errors. Lyapunov stability theory analysis showed that tracking errors and their derivatives were stable and all signals in the closed-loop system were bounded. Comparative simulation results demonstrated the effectiveness and superiority of the proposed scheme, which could be a reference for the design of unmanned underwater vehicle.