Research on Anti-swaying of Crane Based on T-S Type Adaptive Neural Fuzzy Control

被引:0
|
作者
Wang, Zhao [1 ]
Shi, Yuhuan [1 ]
Li, Shurong [2 ]
机构
[1] China Univ Petr, Coll Informat & Control Engn, Qingdao 266580, Peoples R China
[2] Beijing Univ Posts & Telecommun, Automat Sch, Beijing 100876, Peoples R China
来源
PROCEEDINGS OF THE 30TH CHINESE CONTROL AND DECISION CONFERENCE (2018 CCDC) | 2018年
关键词
Adaptive fuzzy neural network; T-S model; SNPRP conjugate gradient method; Anti-swing control;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Aiming at the swing problem of container cranes in the process of loading and unloading cargo, an adaptive neural fuzzy (ANFIS) control method based on Takagi-Sugeno (T-S) model is proposed in this paper. Firstly, the mathematical model of crane trolley-hoist system was established based on Lagrange's equation. Secondly, an improved T-S fuzzy neural network is proposed. Since the SNPRP conjugate gradient method has sufficient descent and global convergence under strong search conditions. In this paper. SNPRP conjugate gradient method is used to tram the premise parameters and the consequent parameters of T-S model. In order to obtain the best controller, the optimal control matrix of the system is obtained by linear quadratic optimal control using the minimum energy as an indicator, so that the neural network is used to train the ANFIS controller. Finally, the trained ANFIS controller is applied in the crane trolley-hoist system for simulation. The results show that this control method in this paper has better control effect and robustness under different rope lengths and different working conditions.
引用
收藏
页码:5503 / 5508
页数:6
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