Computation-Efficient Model Predictive Control Using Sphere Decoding Algorithm for DTP-PMSMs

被引：0

作者：

Chen, Jian ^{[1
]}

Zhang, Zhen ^{[1
]}

Niu, Zhenyong ^{[2
]}

Zeng, Shunqi ^{[2
]}

Han, Ruixue ^{[3
]}

Wu, Yitong ^{[1
]}

Chang, Siyuan ^{[1
]}

机构：

[1] Tianjin Univ, Sch Elect & Informat Engn, Tianjin 300072, Peoples R China

[2] Guangdong Power Grid Co Ltd, Guangzhou Power Supply Bur, Guangzhou 510630, Peoples R China

[3] Tianjin Nav Instruments Res Inst, Tianjin 300131, Peoples R China

来源：

IEEE TRANSACTIONS ON MAGNETICS | 2024年 / 60卷 / 10期

关键词：

Vectors; Costs; Voting; Switches; Harmonic analysis; Prediction algorithms; Decoding; Low computation burden; model predictive control; permanent magnet synchronous motor (PMSM); sphere decoding;

D O I：

10.1109/TMAG.2024.3427690

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Extending the prediction horizon for finite control set model predictive control (FCS-MPC) has shown its advantages on steady-state performance and current distortions. However, its inherently high computational burden brought barriers to implement. Hence, a scheme of sphere decoding algorithm-MPC (SDA-MPC) with preliminary election is proposed for the calculation efficiency and harmonic suppression. The experimental prototype is developed and implemented for dual three phase permanent magnet synchronous motor (DTP-PMSM). Experimental results well agree with the theoretical analysis. In particular, the proposed SDA-MPC scheme significantly reduced the average turnaround time by 21% compared with the exhaustive search algorithm (ESA) under the single step. Moreover, it reduced the ripple in x-y subspace by 14% compared with the conventional SDA with whole control set.

引用

页码：1 / 1

页数：5

共 50 条

[41] An Efficient Model Nonlinear Predictive Control Algorithm Based on Stair-like Control Strategy
Tao, Zheng
Gang, Wu
He Defeng
Yue Dazhi
PROCEEDINGS OF THE 27TH CHINESE CONTROL CONFERENCE, VOL 3, 2008, : 557 - 561
[42] A computationally efficient scheduled model predictive control algorithm for control of a class of constrained nonlinear systems
Kothare, Mayuresh V.
Wan, Zhaoyang
ASSESSMENT AND FUTURE DIRECTIONS OF NONLINEAR MODEL PREDICTIVE CONTROL, 2007, 358 : 49 - +
[43] Optimizing Model Predictive Control horizons using Genetic Algorithm for Motion Cueing Algorithm
Mohammadi, Arash
Asadi, Houshyar
Mohamed, Shady
Nelson, Kyle
Nahavandi, Saeid
EXPERT SYSTEMS WITH APPLICATIONS, 2018, 92 : 73 - 81
[44] Memory-Efficient Explicit Model Predictive Control using Posits
Jugade, Chaitanya
Ingole, Deepak
Sonawane, Dayaram
Kvasnica, Michal
Gustafson, John
2019 SIXTH INDIAN CONTROL CONFERENCE (ICC), 2019, : 188 - 193
[45] Efficient building energy management using distributed model predictive control
Scherer, H. F.
Pasamontes, M.
Guzman, J. L.
Alvarez, J. D.
Camponogara, E.
Normey-Rico, J. E.
JOURNAL OF PROCESS CONTROL, 2014, 24 (06) : 740 - 749
[46] A new weight selection algorithm using SPSA for model predictive control
Cho, Sungmin
Otsuki, Masatsugu
Kubota, Takashi
MECHANICAL ENGINEERING JOURNAL, 2019, 6 (05):
[47] Multiplexed Model Predictive Control Weighting Selection using Genetic Algorithm
Joelianto, Endra
Hernawan, Fikri M.
ICICI-BME: 2009 INTERNATIONAL CONFERENCE ON INSTRUMENTATION, COMMUNICATION, INFORMATION TECHNOLOGY, AND BIOMEDICAL ENGINEERING, 2009, : 435 - 439
[48] Nonlinear model predictive control using symbolic computation on autonomous marine surface vehicle
Jiang, Xiaoyong
Huang, Langyue
Peng, Mengle
Li, Zhongyi
Yang, Ke-ji
JOURNAL OF MARINE SCIENCE AND TECHNOLOGY, 2022, 27 (01) : 482 - 491
[49] Nonlinear model predictive control using symbolic computation on autonomous marine surface vehicle
Xiaoyong Jiang
Langyue Huang
Mengle Peng
Zhongyi Li
Ke-ji Yang
Journal of Marine Science and Technology, 2022, 27 : 482 - 491
[50] An efficient algorithm for collaborative learning model predictive control of nonlinear systemsx2729;
Liu, Yanze
Shen, Dong
ISA TRANSACTIONS, 2022, 121 : 1 - 10

← 1 2 3 4 5 →