應用於電動轉向系統之智慧型控制六相永磁同步馬達驅動系統

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：37

、訪客IP：3.145.33.102

姓名

阮開駿(Kai-Chun Juan) 查詢紙本館藏

畢業系所

電機工程學系

論文名稱

應用於電動轉向系統之智慧型控制六相永磁同步馬達驅動系統
(Intelligent Control of Six-Phase Permanent Magnet Synchronous Motor Drive System for Electric Power Steering System)

相關論文

★ 機場地面燈光更新工程 -以桃園國際機場南邊跑滑道為例	★ 多功能太陽能微型逆變器之研製
★ 應用於儲能系統之智慧型太陽光電功率平滑化控制	★ 利用智慧型控制之三相主動式電力濾波器的研製
★ 應用於內藏式永磁同步馬達之智慧型速度控制及最佳伺服控制頻寬研製	★ 新型每安培最大轉矩控制同步磁阻馬達驅動系統之開發
★ 同步磁阻馬達驅動系統之智慧型每安培最大轉矩追蹤控制	★ 利用適應性互補式滑動模態控制於同步磁阻馬達之寬速度控制
★ 具智慧型太陽光電功率平滑化控制之微電網電能管理系統	★ 高性能同步磁阻馬達驅動系統之寬速度範圍控制器發展
★ 智慧型互補式滑動模態控制系統實現於X-Y-θ三軸線性超音波馬達運動平台	★ 智慧型同動控制之龍門式定位平台及應用
★ 利用智慧型滑動模式控制之五軸主動式磁浮軸承控制系統	★ 智慧型控制雙饋式感應風力發電系統之研製
★ 無感測器直流變頻壓縮機驅動系統之研製	★ 應用於模組化輕型電動車之類神經網路控制六相永磁同步馬達驅動系統

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

[檢視]

[下載]

本電子論文使用權限為同意立即開放。
已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。
請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。

摘要(中)

本論文的研究目的是研製以數位訊號處理器為基礎之智慧型控制六相永磁同步馬達驅動系統，其應用在電動轉向系統上。由於電動轉向系統是一個非線性與時變的系統，控制的準確性對於整個電動轉向系統的參數變化、外力干擾與摩擦力相當敏感。然而電動轉向系統的穩定性是目前最重要的發展議題，因此本論文提出兩種智慧型控制系統，一個是具有線上調整學習速率的改良型差分演化演算法之非對稱歸屬函數之小波模糊類神經網路控制器，另一個是智慧型二階滑動模態控制器，利用非對稱歸屬函數之小波模糊類經網路的線上學習能力與快速收斂的特性來估測電動轉向系統的不確定項，以達到電動轉向系統所需求高的控制性能。最後以DSP(TMS320F28335)實現六相永磁同步馬達驅動系統，並且以實驗結果來驗證所提出的智慧型控制器之可行性。

摘要(英)

The purpose of this thesis is to develop a digital signal processor (DSP) based intelligent control of six-phase permanent magnet synchronous motor (PMSM) drive system for electric power steering (EPS) system. Due to the EPS system is a nonlinear and time-varying system, the control accuracy is very sensitive to the parameter variations and external disturbances. Since the stability of EPS system is the most important issue, two intelligent control systems are proposed in this thesis. First, an improved differential evolution wavelet fuzzy neural network with asymmetric membership function (IDE WFNN-AMF) is proposed, in which the learning rates of IDE WFNN-AMF are adapted online. Then, an intelligent two-order sliding-mode controller (I2OSMC) is proposed, in which the uncertainties of the EPS system is estimated using the WFNN-AMF with online learning and fast convergence capabilities. The above two intelligent controllers can achieve the required high control performance of the EPS system. Finally, the six-phase PMSM drive system is implemented by the DSP TMS320F28335, and some experimental results are illustrated to verify the validity of the proposed intelligent controllers.

關鍵字(中)

★ 六相永磁同步馬達
★ 電動轉向系統
★ 數位訊號處理器
★ 非對稱歸屬函數之小波模糊類經網路
★ 改良型差分演化演算法之非對稱歸屬函數之小波模糊類神經網路
★ 智慧型二階滑動模態控制器

關鍵字(英)

★ Six-phase permanent synchronous motor
★ Electric power steering system
★ Digital signal processor
★ Wavelet fuzzy neural network with asymmetric membership function
★ Improved differential evolution wavelet fuzzy neural network with asymmetric membership functio

論文目次

中文摘要 I
英文摘要 II
誌謝 IV
目錄 V
圖目錄 VIII
表目錄 XII
第一章緒論 1
1.1 研究動機與目的 1
1.2 文獻回顧 1
1.3 論文大綱 4
1.4 論文貢獻 5
第二章六相永磁同步馬達控制系統之硬體介紹 6
2.1 前言 6
2.2 TMS320F28335數位訊號處理器簡介 6
2.3 TMS320F28335週邊功能介紹 9
2.3.1 脈波寬度調變模組 9
2.3.2 中斷訊號 10
2.3.3 類比/數位轉換模組 11
2.3.4 正交編碼器脈衝模組 12
2.3.5 串列周邊介面模組 14
2.4 以DSP為基礎的六相永磁同步馬達控制系統 16
2.4.1 DSP28335控制卡 17
2.4.2 DSP28335介面板 17
2.4.3 週邊電路擴充控制板 18
2.5 週邊擴充控制板之電路 19
2.5.1 類比/數位轉換電壓準位轉換電路 19
2.5.2 脈波寬度調變電壓準位轉換電路 20
2.5.3 過電流保護電路 21
2.5.4 數位/類比轉換電路 23
2.5.5 編碼器之解碼電路 24
第三章應用於電動轉向系統之六相永磁同步馬達驅動系統 25
3.1 前言 25
3.2 六相永磁同步馬達 26
3.3 六相永磁同步馬達數學動態模型 28
3.4 座標轉換之電壓及電磁轉矩方程式 30
3.5 空間向量脈波寬度調變 33
3.6 六相永磁同步馬達控制架構 43
3.7 電動轉向系統 45
3.8 電動轉向系統之數學動態模型 47
3.9 實驗結果與討論 50
第四章利用改良型差分演化演算法之非對稱歸屬函數之小波模糊類神經網路控制系統 58
4.1 前言 58
4.2 改良型差分演化演算法之非對稱歸屬函數之小波模糊類神經網路控制系統 58
4.2.1 非對稱歸屬函數之小波模糊類神經網路 58
4.2.2 非對稱歸屬函數之小波模糊類神經網路線上學習法則 63
4.2.3 使用改良型差分演化演算法作學習速率的調整 67
4.3 實驗結果與討論 72
第五章智慧型二階滑動模態控制系統 84
5.1 前言 84
5.2 電動轉向系統之六相永磁同步馬達數學動態模型 84
5.3 二階滑動模態控制器 86
5.4 非對稱歸屬函數之小波模糊類神經網路估測器 88
5.5 智慧型二階滑動模態控制 91
5.6 實驗結果與討論 99
第六章結論與未來展望 106
6.1 結論 106
6.2 未來展望 108
參考文獻 109
作者簡歷 116

參考文獻

[1] A. E. Cetin, M. A. Adli, D. E. Barkana, and H. Kucuk, “Implementation and development of an adaptive steering-control system,” IEEE Trans. Vehicul. Technol., vol. 59, no. 1, pp. 75-83, 2010.
[2] X. Chen, T. Yang, X. Chen, and K. Zhou, “A generic model-based advanced control of electric power-assisted steering systems,” IEEE Trans. Contr. Syste. Technol., vol. 16, no. 6, pp. 1289-1300, 2008.
[3] M. Parmar and J. Y. Hung, “A sensorless optimal control system for an automotive electric power assist steering system,” IEEE Trans. Indust. Electron., vol. 51, no. 2, pp. 290-298, 2004.
[4] S. Anwar and L. Chen, “An analytical redundancy-based fault detection and isolation algorithm for a road-wheel control subsystem in a steerby-wire system,” IEEE Trans. Vehicul. Technol., vol. 56, no. 5, pp. 2859-2869, 2007.
[5] P. Setlur, J. R. Wagner, D. M. Dawson, and D. Braganza, “A trajectory tracking steer-by-wire control system for ground vehicles,” IEEE Trans. Vehicul. Technol., vol. 55, no. 1, pp. 76-85, 2006.
[6] C. D. Gadda, S. M. Laws, and J. C. Gerdes, “Generating diagnostic residuals for steer-by-wire vehicles,” IEEE Trans. Contr. Syste. Technol., vol. 15, no. 3, pp. 529-540, 2007.
[7] J. C. Salmon and B. W. Williams, “A split-wound induction motor design to improve the reliability of PWM inverter drives,” IEEE Trans. Indust. Appl., vol. 26, no. 1, pp. 143-150, 1990.
[8] R. O. C. Lyra and T. A. Lipo, “Torque density improvement in a six-phase induction motor with third harmonic current injection,” IEEE Trans. Indust. Appl., vol. 38, no. 5, pp. 1351-1360, 2002.
[9] S. Green, D. J. Atkinson, A. G. Jack, B. C. Mecrow, and A. King, “Sensorless operation of a fault tolerant PM drive,” IEE Proc. Electr. Power Appl., vol. 150, no. 2, pp. 117-125, 2003.
[10] F. J. Lin, Y. C. Hung, and M. T. Tsai, “Fault tolerant control for
six-phase PMSM drive system via intelligent complementary
sliding mode control using TSKFNN-AMF,” IEEE Trans. Indust.
Electron., to be published, 2013.
[11] W. Yu and X. Li, “Fuzzy identification using fuzzy neural networks with stable learning algorithms,” IEEE Trans. Fuzzy Syst., vol. 12, no. 3, pp. 411-420, 2004.
[12] F. J. Lin, H. J. Shieh, P. K. Huang, and L. T. Teng, “Adaptive control with hysteresis estimation and compensation using RFNN for piezo-actuator,” IEEE Trans. Ultrason. Ferroelectr. Freq. Contr., vol. 53, no. 9, pp. 1649-1661, 2006.
[13] F. J. Lin, P. H. Chou, C. S. Chen, and Y. S. Lin, “DSP-based cross-coupled synchronous control for dual linear motors via intelligent complementary sliding mode control,” IEEE Trans. Indust. Electron., vol. 59, no. 2, pp. 1061-1073, 2012.
[14] H. Chaoui and P. Sicard, “Adaptive fuzzy logic control of permanent magnet synchronous machines with nonlinear friction,” IEEE Trans. Indust. Electron., vol. 59, no. 2, pp. 1123-1133, 2012.
[15] M. A. Khanesar, E. Kayacan, M. Teshnehlab, and O. Kaynak, “Extended Kalman filter based learning algorithm for type-2 fuzzy logic systems and its experimental evaluation,” IEEE Trans. Indust. Electron., vol. 59, no. 11, pp. 4443- 4455, 2012.
[16] H. Y. Pan, C. H. Lee, F. K. Chang, and S. K. Chang, “Construction of asymmetric type 2 fuzzy membership function and application in time series prediction,” in Proc. Int. Conf. Machine Learning and Cybernetics, pp. 2024-2030, 2007.
[17] K. H. Cheng, C. F. Hsu, C. M. Lin, T. T. Lee, and C. Li, “Fuzzy neural sliding mode control for dc-dc converters using asymmetric gaussian membership functions,” IEEE Trans. Indust. Electron., vol. 54, no. 3, pp. 1528-1536, 2007.
[18] C. H. Lee, T. W. Hu, C. T. Lee, and Y. C. Lee, “A recurrent interval type-2 fuzzy neural network with asymmetric membership functions for nonlinear system identification,” in Proc. IEEE Conf. Fuzzy System, pp. 1496-1502, 2008.
[19] J. Zhang, , G. G. Walter, Y. Miao, and W. N. W. Lee, “Wavelet neural networks for function learning,” IEEE Trans. Signal Process., vol. 43, no. 6, pp. 1485-1497, 1995.
[20] H. Pan and L. Z. Xia, “Efficient object recognition using boundary representation and wavelet neural network,” IEEE Trans. Neural Netw., vol. 19, no. 12, pp. 2132-2149, 2008.
[21] C. H. Lu, “Wavelet fuzzy neural networks for identification and predictive control of dynamic systems,” IEEE Trans. Indust. Electron., vol. 58, no. 7, pp. 3046-3058, 2011.
[22] F. J. Lin, K. H. Tan, and J. H. Chiu, “Active islanding detection method using wavelet fuzzy neural network,” in Proc. 2012 IEEE Intern. Confere. Fuzzy System, pp. 1-8, 2012.
[23] F. J. Lin, K. H. Tan, D. Y. Fang, and Y. D. Lee, “Intelligent controlled three-phase squirrel-cage induction generator system using wavelet fuzzy neural network for wind power,” IET Renewa. Power Generat., to be published, 2013.
[24] R. Storn and K. Price, “Differential evolution-A simple and efficient heuristic for global optimization over continuous spaces,” J. Glob. Optim., vol. 11, no. 4, pp. 341-359, 1997.
[25] J. Yan, C. Guo1, and W. Gong, “Hybrid differential evolution with convex mutation,” Journal of Software, vol. 6, no. 11, pp. 2321-2328, 2011.
[26] A. Slowik, “Application of an adaptive differential evolution algorithm with multiple trial vectors to artificial neural network training”, IEEE Trans. Indust. Electron., vol. 58, no. 8, pp. 3160-3167, 2011.
[27] C. H. Chen, C. J. Lin, and C. T. Lin, “Nonlinear system control using adaptive neural fuzzy networks based on a modified differential evolution,” IEEE Trans. Syste., Man, and Cybernet. -Part C: Applicat. and Revie., vol. 39, no. 4, pp. 459-473, 2009.
[28] S. M. Elsayed, R. A. Sarker, and D. L. Essam, “An improved self-adaptive differential evolution algorithm for optimization problems,” IEEE Trans. Indust. Informat., vol. 9, no. 1, pp. 89-99, 2013.
[29] S. M. Islam, S. Das, S. Ghosh, S. Roy, and P. N. Suganthan, “An adaptive differential evolution algorithm with novel mutation and crossover strategies for global numerical optimization,” IEEE Trans. Syste., Man, and Cybernet. -Part b: Cybernet., vol. 42, no. 2, pp. 482-500, 2012.
[30] B. Xin, J. Chen, J. Zhang, H. Fang, and Z. H. Peng, “Hybridizing differential evolution and particle swarm optimization to design powerful optimizers: A review and taxonomy,” IEEE Trans. Syste., Man, and Cybernet. -Part C: Applicat. and Revie., vol. 42, no. 5, pp. 744-767, 2012.
[31] P. Rocca, G. Oliveri, and A. Massa, “Differential evolution as applied to electromagnetics,” IEEE Anten. and Propagat. Magaz., vol. 53, no. 1, pp. 38-49, 2011.
[32] W. Gong, Z. Cai, C. X. Ling, and H. Li, “Enhanced differential evolution with adaptive strategies for numerical optimization,” IEEE Trans. Syste., Man, and Cybernet. -Part b: Cybernet., vol. 41, no. 2, pp. 397-413, 2011.
[33] B. Y. Qu, P. N. Suganthan, and J. J. Liang, “Differential evolution with neighborhood mutation for multimodal optimization,” IEEE Trans. Evolution. Computat., vol. 16, no. 5, pp. 601-614, 2012.
[34] K. Meng, Z. Y. Dong, and K. P. Wong, “Self-adaptive radial basis function neural network for short-term electricity price forecasting,” IET Gener. Transm. Distrib., vol. 3, no. 4, pp. 325-335, 2009.
[35] J. J. E. Slotine and W. Li, Applied Nonlinear Control. Prentice-Hall, NJ, 1991.
[36] B. Beltran, T. Ahmed-Ali, and M. Benbouzid, “High-order sliding-mode control of variable-speed wind turbines,” IEEE Trans. Indust. Electron., vol. 56, no. 9, pp. 3314-3321, 2009.
[37] A. G. Loukianov, J. M. Cañedo, L. M. Fridman, and A. Soto-Cota, “High-order block sliding-mode controller for a synchronous generator with an exciter system,” IEEE Trans. Indust. Electron., vol. 58, no. 1, pp. 337-347, 2011.
[38] M. Manceur, N. Essounbouli, and A. Hamzaoui, “Second-order sliding fuzzy interval type-2 control for an uncertain system with real application,” IEEE Trans. Fuzzy Syst., vol. 20, no. 2, pp. 262-275, 2012.
[39] F. J. Lin, Y. C. Hung, and M. T. Tsai, “Fault tolerant control for six-phase PMSM drive system via intelligent complementary sliding mode control using TSKFNN-AMF,” IEEE Trans. Indust. Electron., to be published, 2013.
[40] F. Valenciaga and P. F. Puleston, “High-order sliding control for a wind energy conversion system based on a permanent magnet synchronous generator,” IEEE Trans. Energy Convers., vol. 23, no. 3, pp. 860-867, 2008.
[41] A. Pisano, A. Davila, L. Fridman, and E. Usai, “Cascade control of PM DC drives via second-order sliding-mode technique,” IEEE Trans. Indust. Electron., vol. 55, no. 11, pp. 3846-3854, 2008.
[42] A. Girin, F. Plestan, X. Brun, and A. Glumineau, “High-order sliding-mode controllers of an electropneumatic actuator: Application to an aeronautic benchmark,” IEEE Trans. Contr. Syst. Technol., vol. 17, no. 3, pp. 633-645, 2009.
[43] M. Amodeo, A. Ferrara, R. Terzaghi, and C. Vecchio, “Wheel slip control via second-order sliding-mode generation,” IEEE Trans. Intellig. Transportat. Syst., vol. 11, no. 1, pp. 122-131, 2010.
[44] J. Na, X. Ren, and D. Zheng, “Adaptive control for nonlinear pure-feedback systems with high-order sliding mode observer,” IEEE Trans. Neur. Netw. and Learn. Syst., vol. 24, no. 3, pp. 370-382, 2013.
[45] TMS320F28335,TMS320F28334, TMS320F28332, TMS320F28235,
TMS320F28234, TMS320F28232 Digital Signal Controllers (DSCs)
Data Manual, Texas Instruments, June 2007.
[46] 許尚文，”六相永磁式同步電動機之設計與控制”，碩士論文，台灣科技大學電機研究所，民國九十五年。
[47] 吳泰廷，”六相永磁式同步電動機驅動系統之故障後控制策略”，碩士論文，台灣科技大學電機研究所，民國九十八年。
[48] 王俊超，”六相永磁式同步電動機驅動器之分析與設計”，碩士論文，台灣科技大學電機研究所，民國九十四年。
[49] 洪英智，”以FPGA為基礎之類神經網路控制線型超音波馬達”，碩士論文，東華大學電機研究所，民國九十七年。
[50] H. R. Choi and G. H. Choe, “A multiobjective parametric optimization for passenger-car steering actuator,” IEEE Trans. Indust. Electron., vol. 57, no. 3, pp. 900-908, 2010.
[51] F. J. Lin, Y. C. Hung, J. C. Hwang, and M. T. Tsai, “Fault-tolerant control of a six-phase motor drive system using a Takagi-Sugeno-Kang type fuzzy neural network with asymmetric membership function,” IEEE Trans. Power Electron., vol. 28, no. 7, pp. 3557-3572, 2013.
[52] Bartolini G., Ferrara A., Levant A., and Usai E., 1999, On second order sliding mode controllers, Variable structure system, sliding mode and nonlinear control (Lecture notes in control and information sciences; 247), Springer-Verlag, pp329-350
[53] 蔡孟庭，”智慧型錯誤容忍控制六相永磁同步馬達驅動系統之開發”，碩士論文，中央大學電機研究所，民國一百零一年。

指導教授

林法正(Faa-Jeng Lin)

審核日期

2013-8-9

推文