| DSP implementation of a neural network vector controller for IPM motor drives | |
Sun, Yang1; Li SH(李署辉)1; Ramezani, Malek1; Balasubramanian, Bharat2; Bian J(卞晶)3 ; Gao, Yixiang1
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| Department | 工业控制网络与系统研究室 |
| Source Publication | Energies
 |
| ISSN | 1996-1073 |
| 2019 | |
| Volume | 12Issue:13Pages:1-17 |
| Indexed By | SCI ; EI |
| EI Accession number | 20192907187209 |
| WOS ID | WOS:000477034700098 |
| Contribution Rank | 3 |
| Funding Organization | Center of Advanced Vehicle Technology, The University of Alabama |
| Keyword | permanent-magnet synchronous motor (PMSM) vector control approximate dynamic programming (ADP) artificial neural network (ANN) digital signal processor (DSP) implementation real-time control linear and over-modulation |
| Abstract | This paper develops a neural network (NN) vector controller for an interior mounted permanent magnet (IPM) motor by using a Texas Instrument TMS320F28335 digital signal processor (DSP). The NN controller is developed based on the complete state-space equation of an IPM motor and it is trained to achieve optimal control according to approximate dynamic programming (ADP). A DSP-based NN control system is built for an IPM motor drives system, and a high efficient DSP program is developed to implement the NN control algorithm while considering the limited memory and computing capability of the TMS320F28335 DSP. The DSP-based NN controller is able to manage IPM motor control in linear, over, and six-step modulation regions to improve the efficiency of IPM drives and to allow for the full utilization of DC bus voltage with space-vector pulse-width modulation (SVPWM). The experiment results show that the proposed NN controller is able to operate with a sampling period of 0.1ms, even with limited DSP resources of up to 150 MHz cycle time, which is applicable in practical motor industrial implementations. The NN controller has demonstrated a better current and speed tracking performance than the conventional standard vector controller for IPM operation in both the linear and over-modulation regions. |
| Language | 英语 |
| WOS Subject | Energy & Fuels |
| WOS Keyword | ADAPTIVE CRITICS ; PMSM ; PWM ; OVERMODULATION ; TORQUE |
| WOS Research Area | Energy & Fuels |
| Funding Project | Center of Advanced Vehicle Technology, The University of Alabama ; Center of Advanced Vehicle Technology, The University of Alabama |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.sia.cn/handle/173321/25315 |
| Collection | 工业控制网络与系统研究室 |
| Corresponding Author | Li SH(李署辉) |
| Affiliation | 1.Department of Electrical and Computer Engineering, University of Alabama, Tuscaloosa, AL 35401, United States 2.Center for Advanced Vehicle Technologies, University of Alabama, Tuscaloosa, AL 35401, United States 3.Lab. of Networked Control Systems, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China |
| Recommended Citation GB/T 7714 | Sun, Yang,Li SH,Ramezani, Malek,et al. DSP implementation of a neural network vector controller for IPM motor drives[J]. Energies,2019,12(13):1-17. |
| APA | Sun, Yang,Li SH,Ramezani, Malek,Balasubramanian, Bharat,Bian J,&Gao, Yixiang.(2019).DSP implementation of a neural network vector controller for IPM motor drives.Energies,12(13),1-17. |
| MLA | Sun, Yang,et al."DSP implementation of a neural network vector controller for IPM motor drives".Energies 12.13(2019):1-17. |
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| File Name/Size | DocType | Version | Access | License | ||
| DSP implementation o（3701KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Download | |
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