Error-Summation Enhanced Newton Algorithm for Model Predictive Control of Redundant Manipulators

Author:

Zhang Fan1ORCID,Jin Long2ORCID,Luo Xin3ORCID

Affiliation:

1. School of Information Science and Engineering, Lanzhou University, Lanzhou, China

2. Chongqing Key Laboratory of Big Data and Intelligent Computing, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, China

3. Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Gansu Province

Gansu Provincial Youth Doctoral Fund of Colleges and Universities

Fundamental Research Funds for the Central Universities

Supercomputing Center of Lanzhou University

Pioneer Hundred Talents Program of Chinese Academy of Sciences

Special Projects of the Central Government in Guidance of Local Science and Technology Development

Science and Technology Project of Chengguan Discrict of Lanzhou

CAS

Light of West China

Natural Science Foundation of Chongqing

Chongqing Entrepreneurship and Innovation Support Program for Overseas Returnees

CAAI-Huawei MindSpore Open Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

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1. Discrete Data-Driven Control of Redundant Manipulators With Adaptive Jacobian Matrix;IEEE Transactions on Industrial Electronics;2024-10

2. Joint Trajectory Optimization for Redundant Manipulators with Constant Path Speed;2024 American Control Conference (ACC);2024-07-10

3. Distributed and Competitive Coordination of Multi-Robot Based on GD-kWTA Network under Noise-Free Condition;2024 16th International Conference on Advanced Computational Intelligence (ICACI);2024-05-16

4. Data-Driven Model Predictive Control for Redundant Manipulators With Unknown Model;IEEE Transactions on Cybernetics;2024

5. Nonsingular fast terminal sliding mode control of manipulator trajectory tracking based on adaptive finite-time disturbance observer;2023 IEEE International Conference on Mechatronics and Automation (ICMA);2023-08-06

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