臺灣博碩士論文加值系統

風扇風速控制系統係針對建築物空調風扇耗能改善的自製實驗系統，主要目的為減少建物內空調中風扇系統的能量損耗，進而減低碳排放。依據風扇理論風扇消耗功率與風量之立方成正比，即輸出50%風量時僅有使用風扇全功率之12.5%，再藉由加強風量(風速)控制即可在相同的輸出風量情況下，輸出更穩定風量並有效降低風扇耗能。
風扇系統擁有非線性系統之特性，系統中有諸多不確定項，應用古典控制進行操作點線性化僅適宜於操作點附近，且容易遭受非線性系統中的不確定量干擾而使得系統輸出偏離預期命令或失控。因此，本論文使用單晶片微控制器PIC30F4011 建構風扇風速控制之模型，接著建構出外部干擾架構以模擬實際上不確定干擾量影響系統的情形，最後再將非線性控制器導入系統，藉此避免上述情況發生。
非線性控制器主要以二階滑動模式控制器為主，其原因為滑動模式控制器對於抵抗參數變動量以及外部干擾量擁有很好的強健性，又可以改善傳統滑動模式控制嚴重的切跳情形。而主要選取控制器為: (i)Lyapunov Based此種控制器為二階滑動模式中的個別形式，利用系統Lyapunov第二定理，系統為漸近穩定，最終能夠收斂在平衡點，而(ii)Sub-optimal Algorithm、(iii)Drift Algorithm則是運用相平面控制法，據系統狀態的相平面位置再透過適當的切換條件選擇不一樣的子結構，此二方法的好處即為若不知系統參數為何，只要適當選擇狀態的上下界值，系統就可依照著控制法則進行控制量的切換，最終使系統到達收斂點。

The Fan wind speed control system (FS) is a self-made experimental system that is designed to improve the efficiency of the air-condition system in buildings by control methods. According to Fan’s Law, a fan operating at 50% output wind volume requires only 12.5% of the power required at 100% output wind volume. In other words, under the condition of same air speed the system with air speed controller has better efficiency through improving the control ability.
FS is a nonlinear system which has many uncertainties and interference around the system. In classical control, the linearized method is only suitable in a small operating region. The system cannot be controlled or out of control when the parameter variations and external disturbance makes the operating point out of the operating region. Therefore, we use the several nonlinear control algorithms to reduce interference of the uncertainty on microchip controller dsPIC30F4011. The component of external disturbance simulates the situation of tube blocking in the actual system.
The second-order sliding mode control (SOSMC) overcomes the serious chattering phenomenon in conventional sliding mode control method and has good anti-uncertainty ability. In this thesis, we selected three SOSMC algorithms for wind speed control of FS. They are (i)Lyapunov based SOSMC algorithm, (ii)Sub-optimal Algorithm, and (iii)Drift Algorithm. The Lyapunov-based SOSMC guaranteed the stability by the Lyapunov second theorem. Sub-optimal SOSMC and drift SOSMC choose different control laws in phase plane which have different convergent trajectories. Both algorithms have good convergence property in the system parameters unknown if the upper boundary is suitable chosen.

摘要 i
ABSTRACT ii
誌謝 iii
目錄 iv
表目錄 vi
圖目錄 vii
符號說明 x
第一章 緒論 1
1.1 風扇系統背景之簡介 1
1.2 研究動機與目的 2
1.3 文獻回顧 3
1.4 論文架構 5
第二章 風扇系統架構與數學模型 6
2.1 系統架構 6
2.2 風扇系統建模 8
第三章 可變結構控制 13
3.1 滑動模式控制 13
3.2 滑動模式理論 13
3.2.1 滑動條件 16
3.2.2 迫近條件 16
3.3 滑動模式控制之設計技巧 17
3.4 滑動模式控制器設計 20
第四章 二階滑動模式控制 22
4.1 二階滑動模式控制原理 22
4.2 系統相對階數與滑動函數的選擇 22
4.3 二階滑動模式控制器種類 23
4.4 二階滑動模式控制器設計 27
4.4.1 二階滑動模式控制器Sub-optimal Algorithm 27
4.4.2 二階滑動模式控制器Drift Algorithm 33
4.4.3 二階滑動模式控制器Lyapunov-Based 35
第五章 PIC30F4011微控制器 37
5.1 PIC30F4011微控制器介紹 37
5.2 操作範圍 40
5.3 計時器/計數器 41
5.4 高速類比數位轉換器 42
5.5 資料傳輸介面 44
5.5.1 通用非同步接收傳輸模組 44
5.5.2 同步串列通訊傳輸介面 45
第六章 實驗系統 47
6.1 風扇系統之週邊硬體架構 47
6.2 軟體應用 52
第七章 實驗結果 55
7.1 實驗系統參數 55
7.2 實驗結果探討 57
7.2.1 滑動模式控制器Sliding Mode Controller 57
7.2.2 二階滑動模式控制器Sub-optimal Algorithm 61
7.2.3 二階滑動模式控制器Drift Algorithm 68
7.2.4 二階滑動模式控制器Lyapunov-Based 75
7.2.5 實驗結果比較圖 82
第八章 結論與未來研究方向 92
參考文獻 94

[1]吳旭聖、江旭政、楊秉純，空調箱送風量測試方法探討與空調送風耗能研究，電機月刊第十八卷第五期，2008。
[2]吳旭聖、江旭政，空調箱送風量探討與耗能探討研究，電機月刊第十九卷第五期，2009。
[3]賴慶峰、詹全富、郭欽弘，空壓系統之節能改善與案例分析上，機械月刊35卷9期，2009。
[4]ANSI/ASHRAE/IESNA, Energy standard for buildings except low-rise residential buildings, 2004.
[5]經濟部能源局，能源局101年年報，經濟部能源局，2013年。
[6]可變風量空調系統的靜壓重調控制，機電工程署。
[7]何宗岳，變風量空調送風系統之檢討，中華水電冷凍空調月刊，2013。
[8]ASHRAE handbook, HVAC systems and equipment handbook, 2000.
[9]C. J. Munaro, M. R. Filho, R. M. Borges, S. S. Munareto and W. T. Costa, “Modeling and observer-based nonlinear control of a magnetic levitation system,”
IEEE International Conference on Control Applications, Vol. 1, pp. 162-167, 2002.
[10]P. H. Chang and J. H. Jung, “A systematic method for gain selection of robust PID control for nonlinear plants of second-order controller canonical form,” IEEE International on Control Systems Technology, Vol. 17, No. 2, pp. 473-483, 2009.
[11]Z. Zhu, Y. He, J. QI and T. Wang, “The analysis and synthesis of PID controller based on closed loop response characteristics,” IEEE International on Robotics and Biomimetics, pp. 1930-1936, 2012.
[12]J. Y. Parede, F. Guerin and M. Gorka, “Implementation of a phase lead controller on an FPGA target,” IEEE International Symposium on Industrial Electronics, Vol. 1, pp. 205-210, 2006.
[13]J. Fei, “A class of adaptive sliding mode controller with integral sliding surface,” IEEE International Conference on Mechatronics and Automation, pp. 1156-1161, 2009.
[14]J. D. Lee, S. Khoo and Z. B. Wang, “DSP-Based sliding-mode control for electromagnetic-levitation precise-position system,” IEEE Transactions on Industrial Informatics, Vol. 9, No. 2, pp. 818-827, 2013.
[15]H. K. Chiang, C. A. Chen and M. Y. Li, “Integral variable-structure grey control for magnetic levitation system,” IEE Proceedings-Electric Power Applications, Vol. 153, No. 6, pp. 809-814, 2006.
[16]F. J. Lin, L. T. Teng and P. H. Shieh, “Intelligent adaptive backstepping control for magnetic levitation apparatus,” IEEE Transactions on Magnetics, Vol. 43, No. 5, 2007.
[17]許峯瑞，風扇系統之適應步階滑模控制，國立雲林科技大學，碩士論文，2014。
[18]K. R. S. Kodagoda, W. S. Wijesoma, and E. K. Teoh, “Fuzzy speed and steering control of an AGV,” IEEE Transactions on Control Systems Technology, Vol. 10, No. 1, pp. 112-120, 2014.
[19]T. S. Li, S. J. Chang and W. Tong, “Fuzzy target tracking control of autonomous mobile robots by using infrared sensors,” IEEE Transactions on Fuzzy Systems, Vol. 12, No. 4, pp. 491-501, 2004.
[20]Y. Wen and X. Ren, “Neural networks-based adaptive control for nonlinear time-varying delays systems with unknown control direction,” IEEE Transactions on Neural Networks, Vol. 22, No. 10, pp. 1599-1612, 2011.
[21]F. J. Lin, P. H. Shen and Y. S. Kung, “Adaptive wavelet neural network control for linear synchronous motor servo drive,” IEEE Transactions on Magnetics, Vol. 41, No. 12, pp. 1414-1418, 2004.
[22]S. Tong, Y. Li, G. Feng and T. Li, “Observer-based adaptive fuzzy backstepping dynamic surface control for a class of non-linear systems with unknown time delays,” IET Control Theory & Applications, Vol. 5, No. 12, pp. 1426-1438, 2011.
[23]W. Y. Wang, C. Y. Cheng and Y. G. Leu, “An online GA-based output-feedback direct adaptive fuzzy-neural controller for uncertain nonlinear systems,” IEEE Transactions on Systems Man and Cybernetics, Vol. 34, No. 1, pp. 334-345, 2004.
[24]C. M. Lin and C. F. Hsu, “Adaptive fuzzy sliding-mode control for induction servomotor systems,” IEEE Transactions on Energy Conversion, Vol. 19, No. 2, pp. 362-368, 2004.
[25]C. C. Kung and T. H. Chen, “H^∞ tracking-based adaptive fuzzy sliding mode controller design for nonlinear systems,” IET Control Theory, Vol. 1, No. 1, pp. 82-89, 2007.
[26]蔣承鎰，適應類神經網路與灰色滑模控制器應用於風扇板系統，國立雲林科技大學，碩士論文，2012。
[27]M. Jin, J. Lee, P. H. Chang and C. Choi, “Practical nonsingular terminal sliding-mode control of robot manipulators for high-accuracy tracking control,” IEEE Transactions on Industrial Electronics, Vol. 56, No. 9, pp. 3539-3601, 2009.
[28]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 Transactions on Industrial Electronics, Vol. 59, No. 2, pp. 1061-1073, 2012.
[29]F. J. Lin, S. Y. Chen and M. S. Huang, “Intelligent double integral sliding-mode control for five-degree-of-freedom active magnetic bearing system,” IET Control Theory & Applications, Vol. 5, No. 11, pp. 1287-1303, 2011.
[30]A. Levant, “Sliding order and sliding accuracy in sliding mode control,” International Journal of control Automation and System, Vol. 58, No. 6, pp. 1247-1263, 1993.
[31]G. Bartolini, A. Ferrara and E. Usani, “Chattering avoidance by second-order sliding mode control,” IEEE Transactions on Automatic Control, Vol. 43, No. 2, pp. 241-246, 1998.
[32]G. Bartolini, A. Ferrara, A. Levant and E. Usai, “On second order sliding mode controls,” in variable Structure System, Sliding Mode and Nonlinear Control, ser. Lecture Notes in Control and information Sciences, K. D. Young and U.Ozguner, Eds., Godalming: Soringer-Verlag, London Ltd, pp. 329-350, 1999.
[33]N. Zhang, M. Yang, Y. Jing and S. Zhang, “Congestion control for DiffServ network using second-order sliding mode control,” IEEE Transactions on Industrial Electronics, Vol. 56, No. 9, pp. 3330-3337, 2009.
[34]陳永平，可變結構控制設計，全華科技圖書股份有限公司，1999。
[35]R. A. DeCarlo, S. H. Zak and G. P. Matthews, “Variable structure control of nonlinear multivariable systems: a tutorial,” proceedings on the IEEE, Vol. 76, No. 3, pp. 212-232, 1988.
[36]J. Y. Hung, W. Gao and J. C. Hung, “Variable structure control: a survey,” IEEE Transactions on Industrial Electronics, Vol. 40, No. 1, pp. 2-22, 1993.
[37]H. K. Khalil, Nonlinear system, Prentice Hall, 2002.
[38]J. J. Slotine and S. S. Sastry, “Tracking control of non-linear systems using sliding surfaces, with application to robot manipulators,” International Journal of control, Vol. 38, No. 2, pp. 465-492, 1983.
[39]F. J. Lin, K. K. Shyu and Y. S. Lin, “Variable structure adaptive control for PM synchronous servo motor drive,” IEE Proceedings-Electric Power Applications, Vol. 146, No. 2, pp. 173-185, 1999.
[40]郭威宏，高階離散順滑控制，國立成功大學，碩士論文，2003。
[41]M. Mohamadian, M. M. Pedram and F. Ashrafzadeh, “Digital second order sliding mode control for a synchronous reluctance motor,” IEEE Industry Application Conference, pp. 1899-1902, 2004.
[42]G. Bartolini, A. Pisano and E. Usai, “An improved second-order sliding-mode control scheme robust against the measurement noise,” IEEE Transactions on Automatic Control, Vol. 49, No. 10, pp. 1731-1737, 2004.
[43]G. Bartolini, A. Ferrara and E. Usai, “Applications of a sub-optimal discontinuous control algorithm for uncertain second order systems,” International Journal of Robust and Nonlinear Control, Vol. 7, No. 4, pp. 299-319, 1997.
[44]S. V. Emelyanov, S. K. Korovin and L. V. Levantovskiy, “A drift algorithm in control of uncertain processes,” Problem of Control and Information Theory, Vol. 15, No. 6, pp. 425-438, 1986.
[45]曾百由，dsPIC數位訊號控制器原理與應用，宏友圖書開發股份有限公司，2009。
[46]dsPIC30F4011 Data Sheet, dsPIC30F4011/4012 Data Sheet High-Performance 16-Bit Digital Signal Controllers, Microchip Technology Inc, 2010.
[47]dsPIC30F參考手冊，dsPIC30F系列參考手冊， Microchip Technology Inc，2006。
[48]MCP4921/4922 Data Sheet, 12-Bit DAC with SPI™ Interface, Microchip Technology Inc, 2004.
[49]林銘波，微算機基本原理與應用，全華科技圖書公司，2013。
[50]ICD2 User’s Guide, MPLAB ICD2 in-circuit debugger user’s guide, Microchip Technology Inc, 2003.