ROV control based on adaptive non-singular terminal sliding mode active disturbance rejection
This paper proposes a non-singular terminal sliding mode active disturbance rejection control method with parameter variation caused by the uncertainty of the system model and environmental disturbance when the tracked underwa-ter robot works floating.Secondly,a non-singular terminal sliding-mode controller is used to replace the traditional linear self-resisting linear controller to improve the control performance and anti-disturbance capability of the system.The conver-gence rate is adjusted by using a gradient-descent RBF neural network considering the problem of introducing too many parameters,and the stability of the system is proved by Lyapunov's theorem.Finally,the trajectory tracking simulation ex-periments are compared to linear self immunity,rapidity and smoothness of the response process of the system is improved.
sliding mode active disturbance rejectionRBF neural networkparameter adjustmenttrajectory tracking
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