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Neural-network-based two-loop control of robotic manipulators including actuator dynamics in task space
Received:March 24,2008  Revised:September 22,2008
Keywords:Robotic manipulator  Motion control  Neural network  Task space
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Liangyong WANG, Tianyou CHAI, Zheng FANG1 Key Laboratory of Integrated Automation of Process Industry, Northeastern University, Shenyang Liaoning 110004, China; Research Center of Automation, Northeastern University, Shenyang Liaoning 110004, China 
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Abstract:
      A neural-network-based motion controller in task space is presented in this paper. The proposed controller is addressed as a two-loop cascade control scheme. The outer loop is given by kinematic control in the task space. It provides a joint velocity reference signal to the inner one. The inner loop implements a velocity servo loop at the robot joint level. A radial basis function network (RBFN) is integrated with proportional-integral (PI) control to construct a velocity tracking control scheme for the inner loop. Finally, a prototype technology based control system is designed for a robotic manipulator. The proposed control scheme is applied to the robotic manipulator. Experimental results confirm the validity of the proposed control scheme by comparing it with other control strategies.
Liangyong WANG, Tianyou CHAI, Zheng FANG1.Neural-network-based two-loop control of robotic manipulators including actuator dynamics in task space[J].Journal of Control Theory and Applications,2009,7(2):112~118.
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