基於微控制器實現小腦模型之DC/DC轉換器控制

CMAC Control of DC/DC Converter Using Microcontroller

魏金冠(Chin-Kuan Wei)

指導教授 ： 林志民

元智大學/電機通訊學院/電機工程學系/碩士(2007年)

https://doi.org/10.6838/YZU.2007.00292

摘要

本論文目的是基於微控制器實現小腦模型之直流轉直流轉換器控制，整個控制法則包含一小腦模型控制器和一補償控制器兩大部份，前者主要使用一小腦模型類神經網路線上學習一理想控制法則，而後者主要將依據強健控制理論及 追蹤特性達到補償近似誤差所造成之影響。所使用之線上學習法則主要利用到倒傳遞演算法與李雅普諾夫穩定定理推導，此方法的優點在於即時線上學習的能力，對於輸入變動或負載變動較大的受控系統有較佳的控制能力以及適應能力。最後，本論文以PIC18F452微控制器實現所提出控制法則並運用直流轉直流電源轉換器上，經由實驗結果證明所提出之方法優於傳統控制方法。

關鍵字

直流轉直流轉換器 ； 小腦模型控制器 ； 強健控制理論 ； 倒傳遞演算法 ； 李雅普諾夫穩定定理

並列摘要

In this thesis, a CMAC control method of DC/DC converter by using microcontroller approach is proposed. The proposed CMAC control system contains two parts, one is a cerebellar model articulation controller (CMAC) and the other is a robust controller. CMAC is designed to mimic an ideal controller with the tuning of the weights based on the gradient descent method and Lyapunov stability theorem. The robust compensation controller is designed to achieve tracking performance. The advantage of the proposed method is the on-line real-time learning ability. Online learning of the control system can achieve satisfactory control performance and has adaptability to large input variation and load variation of the controlled plant. Finally, the proposed control system is realized by using a PIC18F452 microcontroller. The experimental results show that the proposed control strategy can achieve better performance than conventional PI control.

並列關鍵字

DC/DC converter ； CMAC ； robust control ； gradient descent method ； Lyapunov stability theorem

參考文獻

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