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Precision control of flexible-link manipulator for space operation is challenging due to the dynamics coupling and system uncertainty. In this paper, to deal with system uncertainty and time-varying disturbance,two performance enhanced controller designs, named Composite Learning Control and Disturbance Observer Based Control are presented respectively. To overcome the nonminimum phase, using output redefinition, the dynamics is transformed to two subsystems: internal system and input-output system. For the internal dynamics,the PD(proportion differentiation) control is used with pole assignment. For the input-output subsystem,considering the unknown dynamics, the composite learning control is designed using neural modeling error while in case of disturbance, the disturbance observer based design is proposed. The stability analysis of the closed-loop system is presented via Lyapunov approach. Simulation of 2-degrees of freedom(DOF) flexible-link manipulator is conducted and the results show that the proposed methods can enhance the tracking performance.
Precision control of flexible-link manipulator for space operation is suspended due to the dynamics coupling and system uncertainty. In this paper, to deal with system uncertainty and time-varying disturbance, two performance enhanced controller designs, named Composite Learning Control and Disturbance Observer Based To overcome the nonminimum phase, using output redefinition, the dynamics is transformed to two subsystems: internal system and input-output system. For the internal dynamics, the PD (proportion differentiation differentiation) control is used with pole assignment. For the input-output subsystem, considering the unknown dynamics, the composite learning control is designed using neural modeling error while in case of disturbance, the disturbance observer based design is proposed. The stability analysis of the closed-loop system is presented via Lyapunov approach. Simulation of 2-degrees of freedom (DOF) flexible-link manipulator is conducted and the results show that the proposed methods can enhance the tracking performance.