Abstract
The core issue of automatic manipulator tracking control is how to ensure the given moving target follows the expected trajectory and adapts to various uncertain factors. However, the existing moving target trajectory prediction methods rely on highly complex and accurate models, lacking the ability to generalize different automatic manipulator tracking scenarios. Therefore, this study tries to find a way to realize automatic manipulator tracking control based on moving target trajectory prediction. In particular, a moving target trajectory prediction model was established, and its parameters were optimized. Next, a tracking-training-testing algorithm was proposed for manipulator’s automatic moving target tracking, and the operating flows were detailed for training module, target detection module, and target tracking module. The proposed model and algorithm were proved effective through experiments.
Highlights
With the rapid development of industrial technology, manipulators have been successfully applied to original manual operations, becoming the most widely used manmade tool for industrial production [1,2,3,4,5,6]. e application of manipulators makes production more efficient and flexible. e core issue of automatic manipulator tracking control is how to ensure the given moving target follows the expected trajectory and adapts to various uncertain factors [7,8,9,10,11]
For the trajectory control of Par4 parallel robot, Zhang and Ming [14] designed a type 2 fuzzy predictive compensation proportional-integral-derivative (PID) controller based on the improved dynamic gray wolf optimizer (GWO) based on the mutation operator and the eliminating-reconstructing mechanism (DMR-GWO2). e proposed controller speeds up the response of the parallel robot and improves the adaptability of the entire system
The existing moving target trajectory prediction methods rely on highly complex and accurate models, lacking the ability to generalize different automatic manipulator tracking scenarios [18,19,20,21,22]. erefore, this study develops an approach for automatic manipulator tracking control based on moving target trajectory prediction, aiming to improve the manipulator’s trajectory prediction accuracy and automatic tracking control effect
Summary
E core issue of automatic manipulator tracking control is how to ensure the given moving target follows the expected trajectory and adapts to various uncertain factors. The existing moving target trajectory prediction methods rely on highly complex and accurate models, lacking the ability to generalize different automatic manipulator tracking scenarios. Erefore, this study tries to find a way to realize automatic manipulator tracking control based on moving target trajectory prediction. A moving target trajectory prediction model was established, and its parameters were optimized. A tracking-training-testing algorithm was proposed for manipulator’s automatic moving target tracking, and the operating flows were detailed for training module, target detection module, and target tracking module. E proposed model and algorithm were proved effective through experiments A tracking-training-testing algorithm was proposed for manipulator’s automatic moving target tracking, and the operating flows were detailed for training module, target detection module, and target tracking module. e proposed model and algorithm were proved effective through experiments
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