臺灣博碩士論文加值系統

本研究針對工具機開發一適應性負荷控制技術，用以準確地估測工作平台的轉動慣量與摩擦力參數，並透過伺服參數優化進一步提升加工效能。首先透過掃頻訊號激振機台，透過伺服模型最佳化方法搭配阻尼高斯牛頓演算法法與成本函數求得最佳的系統轉移函數階數，並使用鑑別後的系統模型以及給定的系統規格，藉以優化伺服迴路控制參數。決定伺服控制迴路參數後，即可推導位置輸入對扭矩輸出的轉移函數。可變進給距離來回運動方法透過鐘形加減速命令驅動伺服軸，再利用最小平方法搭配速度與扭矩等量測資訊進行慣量估測與摩擦力參數鑑別。在實機加工進行進退刀時，控制器對於工作台的質量以及轉動慣量可以線上進行慣量估測，用以適應性調整控制器參數。最後，模擬和實驗在一五軸工具機上執行，用來驗證本研究所提出的方法可以同時提升加工效能以及加工精度。

In this study, an adaptive load control method for machine tools is developed to precisely estimate movement of inertia of the workpiece and improve machining performance by means of servo parameter optimization. The nominal plant of the machine is excited by the swept-frequency cosine signal. Servo modeling optimization (SMO) method with damped Gauss-Newton algorithm and cost function minimization is used to obtain the best orders of system transfer function. Based on the precise identified model, controller parameters of servo loops are optimized and correctly set with user-defined specification. Transfer functions from position input to torque output are derived after determining parameters of servo control loops. Back-and-forth movement with variable feedrate and distance (BMVFD) method adopts bell-shaped acceleration/deceleration (ACC/DEC) commands to drive servo axes, and utilizes least mean square method with measured data of velocity and torque to estimate moment of inertia and identify friction parameters. In real machining, the controller can estimate the current mass and the moment of inertia of the workpiece and adaptively adjust the parameters of servo control loops. Finally, simulations and experiments are carried out on a five-axis engraving machine to verify efficiency of the proposed method in improvement of cycle time and machining accuracy.

摘要.............................. i
Abstract........................ ii
誌謝.............................. iv
目錄.............................. v
表目錄.............................. vii
圖目錄.......................... viii
符號說明.......................... x
第一章 緒論.......................... 1
1.1 研究動機與目的................... 1
1.2 文獻探討.......................... 1
1.2.1 工具機建模..................... 1
1.2.2 系統鑑別與伺服調機.............. 2
1.2.3 慣量估測....................... 3
1.2.4 摩擦力鑑別與補償................ 5
1.2.5 伺服迴路設計.................... 5
1.3 研究方法.......................... 7
1.4 論文架構.......................... 7
第二章 工具機台系統鑑別與共振抑制....... 9
2.1 系統鑑別.......................... 9
2.1 系統模型最佳化..................... 10
2.1.2 最小平方法擬合................... 11
2.1.3 阻尼高斯-牛頓法.................. 12
2.2 共振抑制濾波器.................... 15
2.2.1 凹陷濾波器....................... 16
2.2.2 濾波器參數自動調校................ 17
第三章 慣量估測與摩擦力鑑別.............. 19
3.1 摩擦力效應.......................... 19
3.1.1 摩擦力模型....................... 19
3.1.2 中低頻伺服模型.................... 20
3.1.3 黏滯摩擦力鑑別................... 21
3.1.4 庫倫摩擦力鑑別.................... 22
3.2 慣量估測.......................... 23
第四章 五軸機台伺服控制迴路設計......... 24
4.1 伺服控制迴路推導與增益調整........... 24
4.1.2 速度迴路控制器.................... 25
4.1.3 位置迴路控制器.................... 25
4.1.4 速度前饋迴路控制器................ 26
4.2 前饋補償迴路設計.................... 27
4.2.1 加速度前饋迴路控制器.............. 27
4.3 位置到電壓閉迴路轉移函數............ 27
4.3.1 位置到電壓閉迴路轉移函數推導...... 28
4.3.2 電壓輸出解析解.................. 28
第五章 PCB五軸路徑實驗................. 31
5.1 實驗平台.......................... 31
5.1.1 實驗機台.......................... 31
5.1.2 PC-based控制器與人機介面......... 31
5.2 實驗架構.......................... 32
5.3 伺服模型最佳化演算法優化效能測試..... 34
5.4 慣量估測與摩擦力鑑別................ 41
5.5 伺服性能實驗驗證................... 43
5.6 雙軸輪廓循跡實驗................... 44
第六章 結論與未來方向................... 50
參考文獻.......................... 51
附錄一.......................... 57
位置到電壓系統轉移函數.................. 57
附錄二.......................... 62
速度迴路控制器.......................... 62
位置迴路控制器.......................... 63
速度前饋迴路控制器.................... 63
加速度前饋迴路控制器.................... 64
Extended Abstract..................... 66

[1]A. Matsubara, K. Lee, S. Ibaraki and Y. Kakino, “Enhancement of feed drive dynamics of NC machine tools by actively controlled sliding guideway,” JSME International Journal Series C, vol. 47, no.1, pp. 150-159, 2004.
[2]Y. Hori, H. Iseki and K. Sugiura, “Basic consideration of vibration suppression and disturbance rejection control of multi-inertia system using SFLAC (state feedback and load acceleration control),” IEEE Transactions on Industry Applications, vol. 30, no. 4, pp. 889-896, 1994.
[3]Y.-Y. Chen, P.-Y. Huang and J.-Y. Yen, “Frequency-domain identification algorithms for servo system with friction,” IEEE Transactions on Control Systems Technology, vol. 10, no. 5, pp. 654-665, 2002.
[4]K. Lee, S. Ibaraki, A. Matsubara, Y. Kakino, Y. Suzuki, S. Arai and J. Braasch, “A servo parameter tuning method for high-speed NC machine tools based on contouring error measurement,” WIT Transactions on Engineering Sciences, vol. 44, pp. 1-10, 2003.
[5]Y. Altintas, A. Verl, C. Brecher, L. Uriarte and G. Pritschow, “Machine tool feed drives,” CIRP Annals - Manufacturing Technology, vol. 60, no. 2, pp. 779-796, 2011.
[6]A. Matsubara, K. Lee, S. Ibaraki and Y. Kakino, “Enhancement of feed drive dynamics of NC machine tools by actively controlled sliding guideway, ” JSME International Journal Series C, vol. 47, no.1, pp. 150-159, 2004.
[7]Y. Altintas, A. Verl, C. Brecher, L. Uriarte and G. Pritschow, “Machine tool feed drives,” CIRP Annals - Manufacturing Technology, vol. 60, no. 2, pp. 779-796, 2011.
[8]K. Lee, S. Ibaraki, A. Matsubara, Y. Kakino, Y. Suzuki and Y. Yamaoka, “A servo parameter tuning method for high-speed NC machine tools based on contouring error measurement,” WIT Transactions on Engineering Sciences, vol. 44, pp. 12, 2003.
[9]H.-W. Huang, M.-S. Tsai and Y.-C. Huang, “Modeling and elastic deformation compensation of flexural feed drive system,” International Journal of Machine Tools and Manufacture, vol. 132, pp. 96-112, 2018.
[10]邱淑瑞，工具機傳動系統動態分析與振動抑制方法之研究，國立中正大學機械工程研究所，碩士論文，2014。
[11]陳俊堯，工具機傳動系統彈性變形補償與振動抑制，國立中正大學機械工程研究所，碩士論文，2015。
[12]C. H. Yeung, Y. Altintas, and K. Erkorkmaz, “Virtual CNC System. Part I. System Architecture,” International Journal of Machine Tools and Manufacture, vol. 46, no. 10, pp. 1107-1123, 2006.
[13]Y. Altintas, and S. Tulsyan, “Prediction of Part Machining Cycle Times via Virtual CNC,” CIRP Annals -manufacturing Technology, vol. 64, no. 1, pp. 361-364, 2015.
[14]Y. Altintas, P. Kersting, D. Biermann, E. Budak, B. Denkena, and I. Lazoglu, “Virtual Process Systems for Part Machining Operations,” CIRP Annals-manufacturing Technology, vol. 63, no. 2, pp. 585-605, 2014.
[15]C.-H. Lee, M.-Y. Yang, C.-W. Oh, T.-W. Gim and J.-Y. Ha, “An integrated prediction model including the cutting process for virtual product development of machine tools, International Journal of Machine Tools & Manufacturing, vol. 90, pp. 29-43, 2015.
[16]D. Kim, D. H. Son and D. Jeon, “Feed-system autotuning of a CNC machining center: Rapid system identification and fine gain tuning based on optimal search,” Precision Engineering, vol. 36, no. 2, pp. 339-348, 2012.
[17]K. Erkorkmaz and W. Wong, “Rapid identification technique for virtual CNC drives,” International Journal of Machine Tools and Manufacture, vol. 47, no. 9, pp. 1381-1392, 2007.
[18]Y.-Y. Chen, P.-Y. Huang and J.-Y. Yen, “Frequency-domain identification algorithms for servo system with friction,” IEEE Transactions on Control Systems Technology, vol. 10, no. 5, pp. 654-665, 2002.
[19]L. Ljiung, System Identification: Theory for the User. Englewood Cliffs, NJ: Prentice-Hall, 1999.
[20]趙清風，使用MATLAB控制之系統識別，全華圖書股份有限公司，2001。
[21]J. Cui, Z. Chu and D. Wang, “Iterative learning control of high acceleration positioning table via sensitivity identification,” Advances in Mechanical Engineering, vol. 8, no. 2, pp. 1-11, 2016.
[22]C.-C. Fuh and H.-H. Tsai, “Adaptive parameter identification of servo control systems with noise and high-frequency uncertainties,” Mechanical Systems and Signal Processing, vol. 21, no. 3, pp. 1437- 1451, 2007.
[23]M. Gevers, P. Hägg, H. Hjalmarsson and J. Schoukens, “The transient impulse response modeling method and the local polynomial method for nonparametric system identification,” Automatica, vol. 68, pp. 314-328, 2016.
[24]黃建祐，CNC工具機之伺服調機軟體開發，國立虎尾科技大學機械設計工程研究所，碩士論文，2016。
[25]J. Lu, W. Xie and H. Zhou, “Combined fitness function based particle swarm optimization algorithm for system identification,” Computers and Industrial Engineering, vol. 95, pp. 122-134, 2016.
[26]C.-H. Lee and C.-Y. Lin, “Remote servo tuning system for multi-axis CNC machine tools using a virtual machine tool approach,” Applied Sciences, vol. 7, no.8, pp. 776-796, 2017.
[27]FANUC Corp., 65264EN-FANUC Servo Tuning Procedure.
[28]Siemens Corp., EN_B101 Servo Optimization, 2004.
[29]張釗維，工具機伺服進給系統鑑別與模擬分析研究，國立中興大學機械工程研究所，碩士論文，2016。
[30]陳信霖，工具機刀尖點動態特性之系統鑑別與模擬分析研究，國立中興大學機械工程研究所，碩士論文，2016。
[31]徐煒智，以頻域設計伺服馬達之共振抑制與精密控制實現，國立交通大學電機與控制工程研究所，碩士論文，2008。
[32]林業勛，CNC精密伺服運動之遠端診斷與調整系統，國立交通大學電控工程研究所，碩士論文，2015。
[33]梁金聰，以凹陷濾波器對撓性機構之減振控制，國立雲林科技大學機械工程研究所，碩士論文，2012。
[34]劉德葳，PCB機台之伺服模型最佳化與自動調校，國立虎尾科技大學機械設計工程研究所，碩士論文，2017。
[35]林明宗、李孟哲、余坦達、李日傑、陳凌璇、劉德葳、黃建祐，智慧機械與機器人先進控制器技術之研發與應用，全華圖書股份有限公司，2019年4月。
[36]林建佑，五軸工具機雲端智能診斷與自動調機優化基於頻域系統鑑別，國立中興大學機械工程研究所，碩士論文，2017。
[37]H.-W. Chiu and C.-H. Lee, “Prediction of machining accuracy and surface quality for CNC machine tools using data driven approach, ” Advances in Engineering Software, vol. 114, pp. 246-257, 2017.
[38]邱泓維，智慧型加工專家系統:基於CNC控制器參數選擇與優化，國立中興大學機械工程研究所，碩士論文，2017。
[39]廖學佑，智慧化加工表面粗糙度預測模型及材料移除率最佳化研究-以塑膠射出成型模銑削為例，國立中興大學機械工程研究所，碩士論文，2015。
[40]Heidenhain Corporation, Dynamic precision-Machining Dynamically and with High Accuracy, Technical Information, 2013.
[41]https://www.okuma.co.jp/chinese/onlyone/servo-navi/index.html，OKUMA智能化技術。
[42]MAZAK Corporation, Smooth technology, Datasheet, 2016.
[43]K. Liu, C. Hou and W. Hua, “A novel inertia identification method and its application in PI controllers of PMSM drives,” IEEE Access, vol. 7, pp. 13445-13454, 2019.
[44]S. Kim, “A novel inertia identification method and its application in PI controllers of PMSM drives,” IEEE Transactions on Industrial Electronics, vol. 66, no. 1, pp.60-70, 2019.
[45]R. Garrido and A. Concha, “Inertia and friction estimation of a velocity-controlled servo using position measurements,” IEEE Transactions on Industrial Electronics, vol. 61, no. 9, pp. 4759-4770, 2014.
[46]S. Jee and J. Lee, “Real-time inertia compensation for multi-axis CNC machine tools,” International Journal of Precision Engineering and Manufacturing, vol. 13, no. 9, pp.1655-1659, 2012.
[47]Y. Maeda, K. Harata and M. Iwasaki, “A friction model-based frequency response analysis for frictional servo systems,” IEEE Transactions on Industrial Informatics, vol. 14, no. 11, pp. 5146-5155, 2018.
[48]C. Canudas-de-Wit, H. Olsson, K. J. Astrom, and P. Lischinsky, “A new model for control of systems with friction,” IEEE Transactions on Automatic Control, vol. 40, no. 3, pp. 419-425, 1995.
[49]C. Canudas-de-Wit, Comments on “A new model for control of systems with friction,” IEEE Transactions on Automatic Control, vol. 43, pp. 1189-1190, 1998
[50]F. J. T. Vargas, E. R. De Fieri, and E. B. Castelan, “Identification and friction compensation for an industrial robot using two degrees of freedom controllers,” in the 2004 International Conference on Control, Automation, Robotics and Vision, Kunming, China, Dec. 6-9, 2004.
[51]R. Kelly and J. Llamas, “Determination of viscous and coulomb friction by using velocity responses to torque ramp inputs,” in the 1999 IEEE International Conference on Robotics and Automation, Detroit, USA, May 10-15, 1999.
[52]T. Takemura and H. Fujimoto, “Simultaneous identification of linear parameters and nonlinear rolling friction for ball screw driven stage,” 37th Annual Conference on IEEE Industrial Electronics Society, Melbourne, Australia, Nov. 7-10, 2011.
[53]M. R. Popovic, D. M. Gorinevsky, and A. A. Goldenberg, “High-precision positioning of a mechanism with nonlinear friction using a fuzzy logic pulse controller,” IEEE Transactions on Control Systems Technology, vol. 8, no.1, pp. 151-158, 2000.
[54]Y. H. Kim and F. L. Lewis, “Reinforcement adaptive learning neural-net-based friction compensation control for high speed and precision,” IEEE Transactions on Control Systems Technology, vol. 8, no. 1, pp. 118-126, 2000.
[55]劉崇慶，進給系統之摩擦力參數鑑別與動態分析，國立中正大學機械工程研究所，碩士論文，2013。
[56]尤誌緯，LuGre摩擦力模型設計於CNC伺服馬達之微動高速精密運動控制，國立交通大學電控工程研究所，碩士論文，2013。
[57]劉佳怡，系統化調整CNC工具機之LuGre摩擦力補償模型參數，國立交通大學電控工程研究所，碩士論文，2016。
[58]Y. Maeda and M. Iwasaki, “Initial friction compensation using rheology-based rolling friction model in fast and precise positioning,” IEEE Transactions on Industrial Electronics, vol. 60, no. 9, pp. 3865-3876, 2013.
[59]Y. Maeda and M. Iwasaki, Rolling friction model-based analyses and compensation for slow settling response in precise positioning, IEEE Transactions on Industrial Electronics, vol. 60, no. 12, pp. 5841-5853, 2013.
[60]蔡孟勳、袁偉翔、王志偉、黃泓緯、劉崇慶，線性移動平台的摩擦力鑑別方法, 中華人民共和國發明專利，CN10503017A，2016。
[61]C.-C. Liu, M.-S. Tsai and C.-C. Cheng, “Development of a novel transmission engaging model for characterizing the friction behavior of a feed drive system,” Mechanism and Machine Theory, vol. 134, pp. 425-439, 2019.
[62]D. Zhang, Y. Niu, L. Sun and M. Tomizuka, “A position-based friction error model and its application to parameter identification,” IEEE Access, vol. 7, pp. 7759-7767, 2019.
[63]FANUC Corporation, AI Nano CNC for high-speed high-accuracy machining, FANUC Series 31i/32i/30i/35i-MODEL B, FANUC Series 31i-MODEL B5 – Datasheet, 2004.
[64]Siemens Corporation, SINUMERIK 840D/840Di/810D/FM-NC Programming Guide Advanced (PGA) 10.00 Edition, 2003.
[65]Heidenhain Corporation, iTNC530 NC Software 340 490-02, 491-02, 492-02, 493-02 – Technique Manual, 2006.
[66]林明宗，開發具有預視及學習功能之運動控制器，國立中正大學機械工程研究所，博士論文，2007。
[67]黃坤益，五軸刀具路徑插補及動態之研究與分析，國立虎尾科技大學機械設計工程研究所，碩士論文，2013。
[68]M.-T. Lin, C.-L. Yen, M.-S. Tsai, and H.-T. Yau, “Application of robust iterative learning algorithm in motion control system,” Mechatronics, vol. 23, no. 5, pp. 530-540, 2013.
[69]李孟哲，五軸刀具中心點路徑即時預讀與插補技術之研究，國立虎尾科技大學機械設計工程研究所，碩士論文，2016。
[70]M.-T. Lin and S.-K. Wu, “Modeling and improvement of dynamic contour errors for five-axis machine tools under synchronous measuring paths,” International Journal of Machine Tools and Manufacture, vol. 72, pp. 58-72, 2013.