Modified ADRC Design of Permanent Magnet Synchronous Motor Based on Improved Memetic Algorithm

被引:8
作者
Liu, Gang [1 ,2 ,3 ]
Xu, Chuanfang [4 ]
Wang, Longda [4 ]
机构
[1] Inner Mongolia Minzu Univ, Coll Engn, Tongliao 028000, Peoples R China
[2] Jiangxi New Energy Technol Inst, Sch Mech & Elect Engn, Xinyu 338004, Peoples R China
[3] Shanghai Jiao Tong Univ, Dept Automation, Shanghai 200240, Peoples R China
[4] Dalian Jiaotong Univ, Sch Automation & Elect Engn, Dalian 116026, Peoples R China
关键词
permanent magnet synchronous motor; auto disturbance rejection control; improved memetic algorithm; optimal control function; Gaussian mutation; fusion distance; PMSM; CONTROLLER;
D O I
10.3390/s23073621
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
In this paper, a novel modified auto disturbance rejection control (ADRC) design of a permanent magnet synchronous motor based on the improved memetic algorithm (IMA) is proposed. Firstly, there is an obvious system ripple caused by the defect that the optimal control function used in traditional ADRC cannot be differentiable and smooth at the segment point; aiming at weakening the system ripple effectively, the proposed method constructs a novel differentiable and smooth optimal control function to modify the ADRC design. Furthermore, aiming at improving the integration parameters optimization effect effectively, a novel improved memetic algorithm is proposed for obtaining the optimal parameters of ADRC. Specifically, an IMA with high-quality balance based on an adaptive nonlinear decreasing strategy for the convergence factor, Gaussian mutation mechanism, improved learning mechanism with the high-quality balance between competitive and opposition-based learning (OBL) and an elite set maintenance mechanism based on fusion distance is proposed so that these strategies can improve the optimization precision by a large margin. Finally, the experiment results of the PMSM speed control practical cases show that the ADRC based on IMA has an apparent better optimization effect than that of fuzzy PI, traditional ADRC based on the genetic algorithm and an improved ADRC based on improved moth-flame optimization.
引用
收藏
页数:20
相关论文
共 36 条
[1]   Mirror milling trajectory planning for large thin-walled parts based on Fuzzy-ADRC controlled force pre-supporting [J].
Bo, Qile ;
Wang, Pengfei ;
Chai, Xingliang ;
Gong, Yue ;
Li, Xu ;
Li, Te ;
Liu, Haibo ;
Wang, Yongqing .
JOURNAL OF MANUFACTURING PROCESSES, 2023, 85 :192-204
[2]   A Memetic Algorithm for Curvature-Constrained Path Planning of Messenger UAV in Air-Ground Coordination [J].
Ding, Yulong ;
Xin, Bin ;
Zhang, Hao ;
Chen, Jie ;
Dou, Lihua ;
Chen, Ben M. .
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2022, 19 (04) :3735-3749
[3]   Optimization of quantum-inspired neural network using memetic algorithm for function approximation and chaotic time series prediction [J].
Ganjefar, Soheil ;
Tofighi, Morteza .
NEUROCOMPUTING, 2018, 291 :175-186
[4]   Modified model-compensation ADRC controller and its application in PMSM current loop [J].
Gao, Yingning ;
Huo, Xin ;
Ma, Kemao ;
Zhao, Hui .
INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL, 2020, 35 (02) :140-150
[5]   Designing anti-windup PI controller for LFC of nonlinear power system combined with DSTS of nuclear power plant and HVDC link [J].
Gashti, Amin ;
Akbarimajd, Adel .
ELECTRICAL ENGINEERING, 2020, 102 (02) :793-809
[6]   Energy- and Labor-Aware Production Scheduling for Industrial Demand Response Using Adaptive Multiobjective Memetic Algorithm [J].
Gong, Xu ;
Liu, Ying ;
Lohse, Niels ;
De Pessemier, Toon ;
Martens, Luc ;
Joseph, Wout .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2019, 15 (02) :942-953
[7]   Chaotic whale optimization algorithm [J].
Kaur, Gaganpreet ;
Arora, Sankalap .
JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING, 2018, 5 (03) :275-284
[8]   A Novel Memetic Algorithm Using Modified Particle Swarm Optimization and Mesh Adaptive Direct Search for PMSM Design [J].
Lee, Jin Hwan ;
Kim, Jong-Wook ;
Song, Jun-Young ;
Kim, Yong-Jae ;
Jung, Sang-Yong .
IEEE TRANSACTIONS ON MAGNETICS, 2016, 52 (03)
[9]   A least squares support vector machine model optimized by moth-flame optimization algorithm for annual power load forecasting [J].
Li, Cunbin ;
Li, Shuke ;
Liu, Yunqi .
APPLIED INTELLIGENCE, 2016, 45 (04) :1166-1178
[10]   Piezoelectric Multimode Vibration Control for Stiffened Plate Using ADRC-Based Acceleration Compensation [J].
Li, Shengquan ;
Li, Juan ;
Mo, Yueping .
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2014, 61 (12) :6892-6902