[1]Zhao Qingyan,Li Jie,Wu Shun,et al.Dynamic matrix predictive control of manipulators based on genetic algorithms[J].Journal of Zhengzhou University (Engineering Science),2020,41(01):32-37.[doi:10.13705/j.issn.1671-6833.2020.01.005]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
41
Number of periods:
2020 01
Page number:
32-37
Column:
Public date:
2020-03-10
- Title:
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Dynamic matrix predictive control of manipulators based on genetic algorithms
- Author(s):
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Zhao Qingyan; Li Jie; Wu Shun; Tu Haibo; Tang Qirong
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School of Mechanical and Energy Engineering, Tongji University
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- Keywords:
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dynamic matrix predictive controlcontrol matrixgenetic algorithmoffline parameter adjustment
- CLC:
-
-
- DOI:
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10.13705/j.issn.1671-6833.2020.01.005
- Abstract:
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Dynamic matrix predictive control (DMC) is a common method for process control of linear systems. Its control effect is greatly affected by the parameters of its control weighting matrix. Aiming at the off-line parameter adjustment of parameter of control weighting matrix of DMC algorithm, a method of optimizing DMC is presented in this paper and fitness function based on input and output parameters of control system is designed . With a single-joint manipulator as the controlled object, a DMC control system is designed to sample the unit step response of the controlled object and adjust the parameters offline by genetic algorithm. The parameters of the system and the genetic algorithm are verified by simulation then . The results show that the parameters of control weighting matrix of DMC algorithm with better output can be obtained quickly and accurately after optimized using genetic algorithm, which is convenient to use DMC for manipulator control