Finite-time dynamic surface control for induction motors with input saturation in electric vehicle drive systems

被引：26
作者：
Luo, Huijuan [1 ]
Yu, Jinpeng [1 ]
Lin, Chong [1 ]
Liu, Zhanjie [2 ]
Zhao, Lin [1 ]
Ma, Yumei [1 ]
机构：
[1] Qingdao Univ, Coll Automat, Qingdao 266071, Shandong, Peoples R China
[2] Qingdao Haier Biomed Co Ltd, Qingdao 266101, Shandong, Peoples R China
来源：
NEUROCOMPUTING | 2019年 / 369卷
基金：
中国国家自然科学基金;
关键词：
Induction motors; Finite-time; Dynamic surface control; Input saturation; ADAPTIVE FUZZY CONTROL; TRACKING CONTROL; NEURAL-NETWORK; NONLINEAR-SYSTEMS; STABILIZATION;
D O I：
10.1016/j.neucom.2019.08.073
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper proposes a neural networks-based finite-time dynamic surface position tracking control method for induction motors with input saturation in electric vehicle drive systems. Firstly, the neural networks are utilized to approximate the unknown nonlinear functions and the dynamic surface control is used to solve the problem of "explosion of complexity" in traditional backstepping technology. Then, the finite-time control technology is adopted to accelerate the response speed of the system and reduce the tracking error, and the iron losses and input saturation are considered to improve control accuracy. At last, the results of simulation contrast experiments show that the proposed control method realizes ideal tracking effect considering iron losses and input saturation of the induction motors. (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页码：166 / 175
页数：10
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