Research Article
An Optimal Tracking Method for Moving Trajectory of Rigid-Flexible Coupled Manipulator Based on Large Data Analysis
@INPROCEEDINGS{10.1007/978-3-030-67874-6_30, author={Yang Fu-Jian and Wei Tao}, title={An Optimal Tracking Method for Moving Trajectory of Rigid-Flexible Coupled Manipulator Based on Large Data Analysis}, proceedings={Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part II}, proceedings_a={ADHIP PART 2}, year={2021}, month={1}, keywords={Rigid-flexible coupling Manipulator Moving trajectory Tracking method Fuzzy nerve}, doi={10.1007/978-3-030-67874-6_30} }- Yang Fu-Jian
Wei Tao
Year: 2021
An Optimal Tracking Method for Moving Trajectory of Rigid-Flexible Coupled Manipulator Based on Large Data Analysis
ADHIP PART 2
Springer
DOI: 10.1007/978-3-030-67874-6_30
Abstract
The manipulator has dynamic characteristics, and the trajectory tracking system of the manipulator has non-holonomic constraints and various uncertainties, which makes tracking control of the mobile manipulator more difficult. There is a big error in tracking a rigid flexible coupling manipulator with a single neural network. A new method for trajectory optimization tracking of a rigid-flexible coupled manipulator based on big data analysis is proposed. This method takes neural network as the research object, introduces fuzzy control into neural network, optimizes a single neural network, forms a composite method of fuzzy neural network, and uses a hybrid method to track the trajectory of the manipulator. Experimental results show that the tracking error of this method is less than 0.035 rad, which improves the tracking efficiency and improves the tracking accuracy. The method can complete the operation faster and more accurately according to the predetermined trajectory, and has higher practical applicability.
