透過您的圖書館登入
IP:3.15.219.217
  • 學位論文

以DSP晶片實現模糊控制之升壓調節器

Implementing Fuzzy Control Using DSP Chip to Control Boost Regulator

指導教授 : 陳添智
若您是本文的作者,可授權文章由華藝線上圖書館中協助推廣。

摘要


傳統的控制問題常需對真實系統建立數學模型來作精確的數值形式計算處理,一般是以一個或多個微分方程式來敘述控制系統的響應。此類控制系統常以PID(proportional-integral-derivative)控制器來實現[4],雖然其能精確的控制,但是假如遇到較複雜、大型的控制系統或者與使用者有關的知識經驗等,則必須花費大量人力、時間去建構數學模型,甚至有可能因過於繁複而無法建構其數學模型。因此我們不可能把整個控制系統的所有變數列出來,而只能去控制一些影響系統較大的因素。模糊控制利用簡單的“IF-THEN”規則來描述系統即可達到系統控制的目的。 在本論文研究主旨於以開環控制(open-loop control) 與閉環控制(closed-loop control) 探討兩者應用DSP 2407晶片控制的差異。

關鍵字

開環控制 閉環控制

並列摘要


Traditional control methodology makes numerically calculation by mathematical model which use one or more differential equations to describe the system transfer functions.The Proportional-Integral-Derivative controller is more popular case. In spite of its accuracy, precise mathematical model for complex system is hard to build up, and even difficult to be solved. Sometimes, we only need to control some key variables in stead of including all system variables. Fuzzy control just use simple “IF-THEN” rule to describe the system function to achieve system control purpose. In this study, we implement fuzzy control programs into TI DSP 2407 chip, and observe the function difference between open-loop control and closed-loop control when they are individually applied to the boost regulator circuit. For open-loop control, the input voltage order V* is applied to input end, the DSP2407 chip accordingly send out the pulse-width-modulation signal with adjustable duty cycle to order the output voltage adjusting to the preset value. When the input voltage order V* changes, the output voltage will change subsequently. If the system is interfered, then the system may malfunction and can not recovered by itself. For close-loop control, the input voltage order V* is applied to input end, the information of output end voltage Vo will feedback to the DSP 2407 chip, where the fuzzy control program will produce the optimal duty cycle of the PWM signal and make the output end voltage Vo adjusted to the preset value. Even some interference come to the system, it will self-learn and self-adjust to the preset voltage value.

參考文獻


1. Sugeno, M.; “Fuzzy control: Principles, practice and perspectives
2. Yamamoto, H.; Furnhashi, T.; “New fuzzy inference method for symbolic stability analysis of fuzzy control system” Advanced Motion Control, 2000. Proceedings. 6th International Workshop on 30 March-1 April 2000 Page(s):443 – 447.
6. Gang Feng; “A Survey on Analysis and Design of Model-Based Fuzzy Control Systems” Fuzzy Systems, IEEE Transactions on Volume 14, Issue 5, Oct. 2006 Page(s):676 – 697.
8. Kai-Yuan Cai; Lei Zhang; “Fuzzy Reasoning as a Control Problem” Fuzzy Systems, IEEE Transactions on Volume 16, Issue 3, June 2008 Page(s):600 – 614.
10. Shu Hongchun; Sun Xiangfei; Si dajun; “Study of fuzzy controller for voltage and reactive power in substation using rough set theory

延伸閱讀