Knowledge Commons of Institute of Automation,CAS
Neural network-based model predictive tracking control of an uncertain robotic manipulator with input constraints | |
Kang, Erlong1,2,3; Qiao, Hong1,2,4; Gao, Jie1,2,3; Yang, Wenjing5 | |
发表期刊 | ISA TRANSACTIONS |
ISSN | 0019-0578 |
2021-03 | |
卷号 | 109页码:89-101 |
摘要 | This paper proposes a neural network-based model predictive control (MPC) method for robotic manipulators with model uncertainty and input constraints. In the presented NN-based MPC structure, two groups of radial basis function neural networks (RBFNNs) are considered for online model estimation and effective optimization. The first group of RBFNNs is introduced as a predictive model for the robotic system with online learning strategies for handling the system uncertainty and improving the model estimation accuracy. The second one is developed for solving the optimization problem. By taking into account an actor-critic scheme with different weights and the same activation function, adaptive learning strategies are established for balancing between optimal tracking performance and predictive system stability. In addition, aiming at guaranteeing the input constraints, a nonquadratic cost function is adopted for the NN-based MPC. The ultimately uniformly boundedness (UUB) of all variables is verified through the Lyapunov approach. Simulation studies are conducted to explain the effectiveness of the proposed method. |
关键词 | Model predictive control Neural network Robotic manipulator Unknown dynamics Online learning estimation Input constraints |
学科领域 | 控制理论 ; 自动控制技术 |
学科门类 | 工学 ; 工学::控制科学与工程 |
DOI | 10.1016/j.isatra.2020.10.009 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key Research and Development Program of China[2017YFB1300200] ; National Key Research and Development Program of China[2017YFB1300203] ; National Natural Science Foundation of China[91648205] ; National Natural Science Foundation of China[61627808] ; National Natural Science Foundation of China[91948303] ; Strategic Priority Research Program of Chinese Academy of Science[XDB32050100] ; development of science and technology of Guangdong province special fund project, China[2016B090910001] |
项目资助者 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; Strategic Priority Research Program of Chinese Academy of Science ; development of science and technology of Guangdong province special fund project, China |
WOS研究方向 | Automation & Control Systems ; Engineering ; Instruments & Instrumentation |
WOS类目 | Automation & Control Systems ; Engineering, Multidisciplinary ; Instruments & Instrumentation |
WOS记录号 | WOS:000618971000009 |
出版者 | ELSEVIER SCIENCE INC |
七大方向——子方向分类 | 智能机器人 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/43229 |
专题 | 多模态人工智能系统全国重点实验室_机器人理论与应用 |
通讯作者 | Qiao, Hong |
作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Beijing Key Lab Res & Applicat Robot Intelligence, Beijing 100190, Peoples R China 4.CAS Ctr Excellence Brain Sci & Intelligence Techn, Shanghai 200031, Peoples R China 5.Natl Univ Def Technol, State Key Lab High Performance Comp, Changsha 410073, Peoples R China |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Kang, Erlong,Qiao, Hong,Gao, Jie,et al. Neural network-based model predictive tracking control of an uncertain robotic manipulator with input constraints[J]. ISA TRANSACTIONS,2021,109:89-101. |
APA | Kang, Erlong,Qiao, Hong,Gao, Jie,&Yang, Wenjing.(2021).Neural network-based model predictive tracking control of an uncertain robotic manipulator with input constraints.ISA TRANSACTIONS,109,89-101. |
MLA | Kang, Erlong,et al."Neural network-based model predictive tracking control of an uncertain robotic manipulator with input constraints".ISA TRANSACTIONS 109(2021):89-101. |
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