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dc.contributorChing-Chih Tsaien_US
dc.contributor.authorTung, Shun-Liangen_US
dc.identifier.citation[1], 2012-02. [2] R. Yusof, and S. Omatu, "A Multivariable Self-Tuning PID Controllers," International Journal of Control, vol.57, no.6, pp.1387-1403 ,1993. [3] R. Yusof, S. Omatu, and M. Khalid," Self-Tuning PID Control: a Multivariable Derivation and Application," Automatica, vol.30, no.12, pp.1975-1981 ,1994. [4] C. C. Tsai, and C. H. Lu, "Adaptive Generalized Predictive Control of Plastic Extrusion Heating Process," Proc. of 1996 Automatic Control Conference, Taipei, Taiwan, pp.550-557, April ,1996. [5] M. Khalid, S. Omatu, and R. Yuof, "MIMO Furnace Control with Neural Networks," IEEE Transactions on Control System Technology, vol.1, no.4, pp.238-245, December 1993. [6] J. S. Taur, and C. C. Tsai, "Temperature Control of a Plastic Extrusion Barrel Using PID Fuzzy Control, "Proc. of 1995 International IEEE/IAS Confernce on Industrial automation and Emerging Technologies, Taipei, Taiwan, pp.370-375, May 1995. [7] S. Omatu, R. Yusof, K Sinohara and M. Hotta, "Temperature Control for Heating Cylinder by Multivariable STC," IEEE Transaction System Control Information Engeering (in Japanese), vol.5, no.3, pp.102-110 ,1992. [8] C. C. Tsai, and C. H. Lu, “Multivariable Self-Tuning Temperature Control for Plastic Injection Molding Process," IEEE Transaction on Industry Applications, vol.34, no. 2, pp.310-318, March/April 1998. [9] C. C. Tsai, and C. H. Huang, " Model Reference Adaptive Predictive Control for a Variable-Frequency Oil-Cooling Machine,” IEEE Transactions on Industrial Electronics, vol.51, no.2, pp.330-338, 2004 (SCI). [10] C. C. Tsai, S. C. Lin, T. Y. Wang, and F. J. Teng , “Stochastic Model Reference Predictive Temperature Control with Integral Action for an Industrial Oil-Cooling Process,” Control Engineering Practice, 2008. (SCI). [11] C. H. Lu, and C. C. Tsai, “Generalized predictive control using recurrent fuzzy neural networks for industrial processes,” Journal of Process Control, no.1, pp.83-92, 2007 (SCI). [12] C. H. Lu, and C. C. Tsai, “Adaptive Predictive Control with Recurrent Neural Network for Industrial Processes: An Application to Temperature Control of a Variable-Frequency Oil-Cooling Machine," IEEE Transactions on Industrial Electronics, vol.55, no.3, pp.1-9, 2008 (SCI). [13] C. F. Juang, “A TSK-type recurrent fuzzy network for dynamic systems processing by neural network and genetic algorithms,” IEEE Trans. Fuzzy Syst., vol. 10, no. 2, pp. 155–170, April. 2002. [14] C. F. Juang, and J. S. Chen, “A Recurrent Fuzzy-Network-Based Inverse Modeling Method for a Temperature System Control,” IEEE Transactions on Systems, Man and Cybernetics—Part C: Applications and Reviews, vol.37, no. 3, May 2007. [15] B. C. Kuo, Digital Control Systems, 2nd Edition, Saunders College Publishing, International Edition, 1992. [16] C. C. Tsai, T. Y. Wang, Z. C. Wang, and C. Y. Lai,“ Two Degree-of-Freedom Control for Constant Continuous Positive Airway Pressure of an Obstructive Sleep Apnea Treatment System,” Journal of Chinese Institute of Engineers, vol. 31, no. 6, pp. 943-953,2008. [17], 2012-02. [18] J. P. Gerry, "A Comparison of PID Control Algorithm," Control Engineering, pp.102-105, March 1987. [19] J. G. Ziegler, and N. B. Nichols, "Optimal Settings For Automatic Controllers," Trans. ASME, pp.759-768, November. 1942. [20] C. C. Hang, K. J. Astrom, and W. K. Ho, "Refinements of the Ziegler-Nichols Tuning Formula," IEE Proc.-D, vol.138, no.2, March 1991. [21] G. H. Cohen, and G. A. Coon, "Theoretical Considerations Of Retarded Control," Trans, ASME, vol.75, pp.827-836, 1953. [22] A. Kaya and, T. J. Scheib, "Tuning of PID Controls of Different Structures, "Control Engineering, pp.62-65, July 1988. [23] M. Yuwana, and D. E. Seborg, "A New Method for On-Line Controller Tuning," AIchE Journal, vol.28, no.3, May 1982. [24] J. N. Koivo, and J. Sorvari, "On-Line Tuning of A Multivariable PID Controller for Robot Manipulators," Proc, 24th IEEE Conf. on Decision & Control, Ft. Lauderdale, FL. pp.1502-504, December. 1985. [25] V. J. Vandoren, "Inside Self-Tuning PID Controllers," Control Engineering, pp. 67-70, August 1993. [26] P. J. Grawthrop, and P. E. Nomikos, "Automatic Tuning of Commercial PID Controllers for Single-Loop and Multiloop Applications," IEEE Control Systems Magazine, pp.34-42, January. 1990. [27] F. Cameron, and D. E. Seborg, " A Self Tuning Controller with a PID Structure," Int. J. Cont., vol. 30, pp. 401-417, 1981. [28] R. Ortega, and R. Kelly, "PID Self-Tuner: Some Theoretical and Practical Aspects," IEEE Trans. Industrial Electronics, vol. 31, no. 4, pp. 332-337, November. 1984. [29] P. J. Gawthrop, "Self-Tuning PID Controllers : Algorithms and Implementation," IEEE Tran. Automt. Contr., vol.31, no.3, pp.201-09, 1986. [30] F. Radke, and R. Isermann, "A Parameter-Adaptive PID-Controller with a Stepwise Parameter Optimization," Automatica, vol. 23, no. 4, pp. 449-457, 1987. [31] P. Vega, C. Prada,and V. Aleixandre, "Self-Tuning Predictive PID controller, " IEE proceeding, vol. 138, no, 3, pp. 303-311, May 1991. [32] T. Yamamoto, S. Omatu, and M. Haneda, "A Design of Self-Tuning PID Controllers," in Proceeding of ACC, pp. 3263-3267, Baltimore, Mayland, June 1994. [33] R. Yusof, and S. Omatu," A Multivariable Self-Tuning PID Controllers," Int. J. Control, vol. 57, no.6, pp.1387-1403, 1993. [34] S. Omatu et al, " Temperature Control for Heating Cylinder by Multivariable STC," Trans. Syst. Contr. Inform. Eng. (in Japanese), vol. 5, no. 3, pp. 102-110,1992. [35] R. Yusof, S. Omatu, and M. Khalid," Self-Tuning PID Control: a Multivariable Derivation and Application," Automatica, vol. 30, no.12, pp.1975-1981, 1994. [36] C. H. Lu, and C. C. Tsai, "Multivariable Self-Tuning Temperature Control for a Plastic Injection Molding Process,"in Proc. 1995 International IEEE/IAS Conf. on Industrial Automation and Emerging Technologies, pp. 702-709, May 1995. [37] J. H. Liao, C. C. Tsai, and H. C. Chang, "Adaptive Predictive PI Temperature Control for Injection Molding Processes, "poceedings of the 1986 Int. Conf. on Automation Technology, July 1996. [38] K.J.Astrom, and T.Hagglund ," Automatic Tuning of Simple Regulators with Specifications on Phase and Amplitude Margins, " Automatica, vol. 20, no. 5, pp. 645-651, 1984. [39] S. J. Qin, "Auto-Tuned Fuzzy Logic Control ,"In Proceeding 1994 of American Control Conference , Baltimore, Maryland, pp. 2465-2469, June 1994. [40] R. Doraiswami, and J. Jiang, "Performance Monitoring in Expert Control Systems,"Automatica, vol.25, no.6, pp.799-811, 1989. [41] K. J. Amstrom, C. C. Hang, P. Persson, and W. K.Ho," Towards Intelligent PID Control," Automatica, vol. 28, no. 1, pp. 1-9, 1992. [42] B. Porter, A. H. Jones, and C. B. Mcheown, "Real-time Expert Tuners for PI Controllers,"IEE Proc.-D, vol.134, no.4, July 1987. [43] T. W. Kraus, and T. J. Myron, "Self-Tuning PID Controller Uses Pattern Recognition Approach," Control Engineering, pp.106-111, June 1984. [44] J. Litt,"An Expert System To Perform On-Line Controller Tuning," IEEE Control Syst. Mag.,pp. 18-23,April 1991. [45] A. E. B. Rnano, P. J. Fleming, and D. I. Jones ,"Connectionist Approach To PID Autotuning," IEE Proceedings-D, vol. 139, no. 3, pp. 279-285, May,1992. [46] S. Tzafestas, and N. P. Papanikolopoulos, "Incremental Fuzzy Expert PID Control," IEEE Tran. Industrial Electronics, vol.37, no.5, pp.365-371, October. 1990. [47] G. M Abdelnour, C. H. Chang, F. H. Huang, and Y.Cheung," Design Of Fuzzy Controller Using Input And Output Mapping Factors," IEEE Trans. On Systems, Man, and Cybernetics, vol. 21,no. 5, pp. 952-959, September./October., 1991. [48] T. H. Lee, C. C. Hang , W. K. Ho, and P. K. Yue, "Implementation of a Knowledge-based PID Auto-Tuner," Automatica, vol. 29, no. 4, pp. 1107-1113, 1993. [49] I. Y. Zhao, M. Tomizuka, and S. Isaka, "Fuzzy Gain Scheduling of PID Controllers," IEEE Trans. on System, Man, and Cybernetics, vol.23, no.5, September/October. 1993. [50] K. L. Anderson, G. L. Blankenship, and L. G. Lebow, "A Rule-based Adaptive PID Controllers," Proc. 27th IEEE conf. Decision, and Control, pp.564-569, 1988. [51] H. C. Tseng, and V. H. Hwang, " Servocontroller Tuning with Fuzzy Logic," IEEE Trans. Contr. Syst. Technology, vol.1, no. 4, pp. 262-269, December. 1993. [52] P.-C. Chen, The Application of Fuzzy-PID Controller on the Mechanical Systems, Ph.D Dissertation, National Cheng-Kung University, 1993. [53] M. Khalid, S. Omatu, and R. Yuof, "MIMO Furnace Control with Neural Networks, " IEEE Trans. Contr. Syst. Technology, vol. 1, no. 4, pp. 238-245, December. 1993. [54] J. S. Taur, and C. C. Tsai, "Temperature Control of a Plastic Extrusion Barrel Using PID Fuzzy Control," Proc. 1995 International IEEE/IAS Conf. on Industrial Automation and Emerging Technologies, pp. 370-375, May 1995. [55] M. Zhao, "Neural-Net-Based Adaptive PID Regulator with Atteuating Excitation Signal,"in Proceeding of 1994 American Control Conference, pp. 2931-2932, Baltimore, Mayland, June 1994. [56] C. C. Tsai, and Y. L. Chang, " Self-Tuning PID Control Using Recurrent Wavelet Neural Networks," Proceeding of the 2012 IEEE International conference on System Man and Cybernetics, Seoul , Korea, October 14-17, 2012. [57] Y. P Hsu, and C. C. Tsai, "Autotuning for Fuzzy-PI Control Using Genetic Algorithm," Proc. of the 22nd Annual International Conf. of the IEEE Industrial Electronics, August 1996. [58] K. J. Astrom, and B. Wittenmark, Adaptive control (2nd ed.). New York: Addison Wesley, 1995 [59] D. W. Clarke, C. Mohatadi, and P. S. Tuffs, "Generalized Predictive Cotrol:Part I and Part II," Automatica, vol.23, no.2, pp.137-160 ,1987. [60] T. Yamamoto, S. Omatu, and M. Haneda, "A Design of Self-Tuning PID Controllers, " Proc. of 1994 American Control Conference, Baltimore, Mayland, pp.3263-3267, June 1994 [61] P. R. Banerjee, and S. L. Shan, "Robust Stability of GPC as Applied to a First Order Model with Delay ," Proc. of 1995 American Control Conference, Seattle, Washington, pp.2884-2889, June 1995. [62] T. C. Hsia, System Identification, Lexington Books ,1979. [63] C. H. Lu, and C. C. Tsai, "Adaptive decoupling predictive temperature control for an extrusion barrel in a plastic injection molding process,” IEEE Transactions on Industrial Electronics, vol. 48, no.5, pp. 968-975, October 2001. [64] W. S. Su, and C. C. Tsai, "Discrete-time VSS Temperature Control for a Plastic Extrusion Process with Water Cooling Systems,” IEEE Transactions on Control System Technology, vol.9, no.4, pp.618-623, July 2001. [65] C. C. Tsai, and C. H. Lu, "Design and Implementation of an Adaptive Generalized Predictive PID Temperature Controller for a Plastic Extrusion Heated Barrel,” Journal of Technology, vol.13, no. 1,pp.167-178, 1998. [66] P. Vega, C. Prada, and V. Aleixandre, "Self- Tuning Predictive PID controller," IEE Proc. D., vol.138, no.3, pp.303-311,1991 [67] R. M. Miller, K. E. Kwok, S. L. Shan, and R. K. Wood, "Development of a Stochastic Predictive PID Controller," Proc. of 1995 American Control Conference, Seattle, Washington, pp.4204-4208, June 1995. [68] J. H. Liao, C. C. Tsai, and H. C. Chang, "Adaptive Generalized Predictive PI Control of Injection Molding Processes," Proc. of the 4th International Conference on Automation Technology, Hsinchu, Taiwan, pp.711-718, July 1996. [69] A. Ollero, A. Garcia-Cerezo, and J. L. Martinez, “Fuzzy Supervisory Path Tracking of Mobile Robots,” in Proc. IFAC Intelligent Autonomous Vehicles, Southampton, U.K., pp. 275-280, 1993. [70] C. C. Tsai, and C. H. Lu, “Fuzzy Supervisory Predictive PID Control of a Plastics Extruder Barrel," Journal of Chinese Institute of Engineers, vol.21, no. 5, pp. 619-624, 1998. [71] Y. L. Chang, C. C. Tsai, “A Fuzzy Supervised Generalized Predictive PID Temperature Control with Feedforward Control for PET Blow Molding Machines,” Proceedings of 2009 CACS International Automatic Control Conference, Taipei, Taiwan, November. 27-29, 2009. [72] Y. L. Chang, and C. C. Tsai, “Stochastic Adaptive Predictive Temperature Control for PET Blow Molding Machines,” Proc. of the 5th IEEE Conference on Industrial Electronics and Applications (ICIEA 2010), Taichung, Taiwan, June 2010. [73] B. Widrow, and E. Walach, Adaptive Inverse Control, Prentice Hall PTR, Upper Saddle River, New Jersey, 1996. [74] C. C. Tsai, and Y. L. Chang, " Two-degrees-of-freedom Control Using Recurrent Fuzzy Neural Networks for a Class of Nonlinear Discrete-Time Time-Delay Systems," Proc. of 2012 IEE International conference on System Science and Engineering, Dalian, China, June 30-July 2, 2012.en_US
dc.description.abstract本論文的目的是針對吹瓶技術(Blow molding)之溫度控制問題,發展兩種雙自由度數位控制法則,使聚酯(PET)瓶胚通過加熱箱後的溫度能控制於目標溫度值與其性能規格之內,以達成吹瓶的穩定性。第一種雙自由度數位溫度控制是由一改善暫態性能之增益前饋控制器,將系統響應快速追蹤至參考設定值,以及一消弭溫度誤差並抵抗外部干擾之閉迴路反饋PID數位控制所構成;其特點為保有傳統溫控師的專家經驗,以及具有PID控制器結構簡單、操作容易等優點。第二種雙自由度數位溫度控制器是由使用徑向基底函數類神經網路(RBFNN)之自調整數位PID控制器與前述的穩態增益前饋控制器所構成;該控制器的最大特色是以RBFNN為基礎的,藉由RBFNN線上學習受控體增量控制之動態數學模型,進而發展出閉迴路反饋PID數位控制器的三參數之自調整律;另一特色是所提的RBFNN數位雙自由度數位控制法則可推廣應用於工業界非線性受控程序。電腦模擬與實驗測試結果皆顯示兩雙自由度數位控制器皆可得到相當不錯的溫控成果與性能。zh_TW
dc.description.abstractThis thesis presents two novel two-degree-of-freedoms stable digital controllers for a PET blow molding machine, in order to achieve satisfactory temperature control of the PET embryo passing through both heating boxes. This first type of controller is composed of a feedforward controller used to improve the transient performance, and a feedback Proportional-Integral-Derivative (PID) controller employed to eliminate remaining temperature errors and achieve disturbances rejection. Such a controller not only retains the practical expertise of the control practitioners working for PET blow molding machines, but also takes advantages of simple structure and easy operation of the conventional PID controller. The second kind of controller consists of a self-tuning PID controller whose three-term parameters are tuned by radial basis function neural networks (RBFNN), and the aforementioned feedforward controller. The second controller not only can automatically tune the three-term parameters by on-line learning the dynamic mathematical model of controlled plants, but also can extend to control a class of nonlinear industrial plants. Moreover, simulations and experimental results are conducted to show the effectiveness and merit of the proposed controllers with capabilities of set-point tracking and disturbance rejection.en_US
dc.description.tableofcontents目 錄 中文摘要 i Abstract ii 目 錄 iii 圖目錄 vii 表目錄 xi 符號對照表 xii 縮寫對照表 xiv 專有名詞對照表 xv 第一章 緒論 1 1.1 前言 1 1.2研究動機與目的 5 1.3文獻回顧 6 1.4主要貢獻 16 1.5章節組織 16 第二章 PET吹瓶機溫控系統設計 18 2.1前言 18 2.2系統架構與關鍵元件 19 2.2.1 PET吹瓶生產系統 19 2.2.2 溫控系統與元件介紹 22 a.紅外線加熱燈箱 23 b.SCR驅動控制模組 24 c.鼓風機 25 d.鼓風機之定溫限制器 26 e.紅外線溫度感測器 27 f.DS1104 R&D 控制板 28 2.2.3設備操作方式與規範 33 2.3控制架構 34 2.4本章結論 35 第三章 雙自由度數位控制設計、模擬與實驗 37 3.1前言 37 3.2雙自由度數位控制器設計 38 3.2.1系統辨識與建模 38 3.2.2前饋控制器設計 40 3.2.3閉迴路反饋PID數位控制器設計 42 a. Ziegler-Nichols參數調整法 44 b.數位PID控制器頻域設計 46 3.2.4雙自由度數位控制器合成 50 3.3電腦模擬與討論 51 3.4實驗成果與討論 53 3.5本章結論 56 第四章 使用RBFNN類神經網路之數位雙自由度控制器設計、模擬與實驗 57 4.1前言 57 4.2使用RBFNN之自調整 PID 控制器設計 61 4.2.1系統受控體與控制法則建構 62 4.2.2徑向基底類神經網路(RBFNN) 62 a.輸入層 63 b.隱藏層 64 c.輸出層 64 d.RBFNN之網路參數更新法則 65 4.2.3使用RBFNN進行PID 控制參數更新的調整機制 66 4.3使用RBFNN之雙自由度數位控制器設計 67 4.3.1雙自由度數位控制法則建構 67 4.3.2使用RBFNN進行雙自由度數位控制參數更新的調整機制 68 4.4電腦模擬與討論 69 4.4.1使用ARMAX非線性模型進行驗證 69 a.單獨使用數位PID控制器 70 b.使用RBFNN之參數自調整數位PID控制器 71 4.4.2兩PID數位控制器性能比較 72 4.4.3兩雙自由度數位控制器性能比較 74 4.5實驗成果與討論 76 4.6本章結論 79 第五章 結論與未來展望 80 5.1結論 80 5.2 未來研究建議 81 參考文獻 82zh_TW
dc.subjectTemperature controlen_US
dc.subjectPID controlen_US
dc.subjectTwo degree of freedom controlen_US
dc.subjectDelay systemen_US
dc.titleDesign and Experimentation of Digital Two-Degree-of-Freedoms Temperature Controllers for PET Blow Molding Machinesen_US
dc.typeThesis and Dissertationzh_TW
item.openairetypeThesis and Dissertation-
item.fulltextno fulltext-
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