Modular Position/Force Control for
 Environmental Constrained Reconfigurable Manipulator

Abstract

Abstract: This paper proposed an adaptive neural network modular position/force control method for environmental constrained reconfigurable manipulator. Mapping the endpoint force of the reconfigurable manipulator to each joint module, describe the entire dynamic model by a set of interconnected subsystems by coupling torques, and the position and contact force of the endpoint should be obtained by controlling the angle and torque of each subsystem. By virtue of the neural networks, the nonlinear and interconnected items are estimated, and the weights of these neural networks can be adaptively updated on line, meanwhile, the estimated errors are removed by a sliding mode control item, and the stabiltiy of the closedloop system should be granteed. Finally, the numerical simulation on two different 2DOF reconfigurable manipulators shows the effectiveness of the proposed method without changing control parameters.

Key words: reconfigurable manipulator； environmental constraint； modular control； position/force control； neural network

CLC Number:

TP 24

LI Yuanchun1,SONG Yang2,ZHAO Bo1,3. Modular Position/Force Control for
Environmental Constrained Reconfigurable Manipulator[J]. Journal of Shanghai Jiao Tong University, 2017, 51(6): 709-714.

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