Optimal Dynamics Control in Trajectory Tracking of Industrial Robots Based on Adaptive Gaussian Pseudo-Spectral Algorithm

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Bibliografske podrobnosti
izdano v:Algorithms vol. 18, no. 1 (2025), p. 18
Glavni avtor: Zhang, Jing
Drugi avtorji: Zhu, Xiaokai, Chen, Te, Dou, Guowei
Izdano:
MDPI AG
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100 1 |a Zhang, Jing  |u School of Mechanical, Electrical and Automotive Engineering, Xuchang Vocational Technical College, Xuchang 461000, China; <email>zhukai1979@outlook.com</email>; Henan Modern Electromechanical Equipment System Integration and Digital Engineering Research Center, Xuchang Vocational Technical College, Xuchang 461000, China 
245 1 |a Optimal Dynamics Control in Trajectory Tracking of Industrial Robots Based on Adaptive Gaussian Pseudo-Spectral Algorithm 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a A pseudo-spectral control algorithm based on adaptive Gauss collocation point reconstruction is proposed to efficiently solve the optimal dynamics control problem of industrial robots. A mathematical model for the kinematic relationship and dynamic optimization control of industrial robots has been established. On the basis of deriving the Legendre–Gauss collocation formula, a two-stage adaptive Gauss collocation strategy for industrial robot dynamics control variables was designed to improve the dynamics optimization control effect of industrial robot by improving the solution efficiency of constrained optimization problems. The results show that compared with the control variable parameterization method and the traditional Gaussian pseudo-spectral method, the proposed dynamic optimal control method based on an adaptive Gaussian point reconstruction algorithm can effectively improve the solving time and efficiency of constrained optimization problems, thereby further enhancing the dynamic optimization control and trajectory tracking effect of industrial robots. 
653 |a Control theory 
653 |a Spectral control 
653 |a Kinematics 
653 |a Collocation methods 
653 |a Motion control 
653 |a Reconstruction 
653 |a Tracking 
653 |a Optimal control 
653 |a Energy consumption 
653 |a Efficiency 
653 |a Industrial robots 
653 |a Spectral methods 
653 |a Adaptive algorithms 
653 |a Parameterization 
653 |a Control algorithms 
653 |a Dynamic programming 
653 |a Coordinate transformations 
653 |a Trajectory optimization 
653 |a Lagrange multiplier 
653 |a Robot dynamics 
653 |a Design 
653 |a Control methods 
653 |a Constraints 
653 |a Optimization algorithms 
653 |a Collocation 
653 |a Robot control 
653 |a Underwater robots 
700 1 |a Zhu, Xiaokai  |u School of Mechanical, Electrical and Automotive Engineering, Xuchang Vocational Technical College, Xuchang 461000, China; <email>zhukai1979@outlook.com</email>; Henan Modern Electromechanical Equipment System Integration and Digital Engineering Research Center, Xuchang Vocational Technical College, Xuchang 461000, China 
700 1 |a Chen, Te  |u Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China; <email>1000005564@ujs.edu.cn</email> 
700 1 |a Dou, Guowei  |u School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China; <email>dgwujs@126.com</email> 
773 0 |t Algorithms  |g vol. 18, no. 1 (2025), p. 18 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3159222893/abstract/embedded/75I98GEZK8WCJMPQ?source=fedsrch 
856 4 0 |3 Full Text + Graphics  |u https://www.proquest.com/docview/3159222893/fulltextwithgraphics/embedded/75I98GEZK8WCJMPQ?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3159222893/fulltextPDF/embedded/75I98GEZK8WCJMPQ?source=fedsrch