Abstract
The China Fusion Engineering Test Reactor (CFETR) multipurpose overload robot (CMOR) is an important part of the CFETR remote handling (RH) system. It is a type of serial robot with a redundant degree of freedom and heavy loads. Due to its long cantilever and heavy load, the deformation is large during operation. However, the deformation of the CMOR in the RH application cannot be ignored. In this paper, an online precision control algorithm using a deformation model is presented. Using this algorithm, the deformations of the CMOR at a limited number of positions are calculated by finite element analysis and used as training datasets. The joint parameters and loads are used as inputs, and the actual position of the CMOR is the output of the Back Propagation Neural Network (BPNN). The deformation model is trained by the BPNN offline, which can calculate the actual position in the workspace. The deformation of the CMOR can be accurately obtained and rapidly compensated to realize online precision control. During the RH operation in the CFETR, the deformation was updated to 2 Hz and the precision control accuracy was up to 5 mm.
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