透過您的圖書館登入
IP:3.145.108.9
  • 期刊

模糊與類神經理論切換應用於適應性參考模式之研究

A Study Applying Fuzzy Theorem & Neural Network on Model Reference Adaptive Control System

摘要


本研究之主要的目的乃是以適應性控制為主要架構,並結合模糊理論與類神經網路原理作為控制器之設計理念,以期能使受控系統之響應達到快速且準確的要求。 目前有關於模楜理論與類神經網路應用於控制上之研究已有許多,但這些研究成果都各自有一些尚待解決之問題,如暫態響應不是一個完美的追隨(Perfect Follow),穩態誤差(Steady State Error)之存在,模楜法則不易求得,學習時間過長等等。基於上述之缺點,引發本論文研究之動機乃是希望能藉著結合模糊與類神經網路理論之優點而以建立一多架構(Multi-Structure)之方式並配合適應性控制以切換方式,期能澈底改善上述之缺點,以期能使受控系統之響應達到快速且準確的要求。

並列摘要


The purpose of this research is to propose an adaptive mode following control system combine fuzzy with neural theory in order to make the characteristics of plants output response completely tracking to the reference model's output response. The fundamental concepts of this approach is that we introduce a multi-structure system and divide this adaptive model reference control system into fast and slow modes. In this situation, a neuro controller is designed to improve the fast modes transient response and a fuzzy controller is designed to improve the steady state error caused by slow modes. The simulation results show that the idea we proposed is really work.

被引用紀錄


邱毓鵬(2005)。學習速率在倒傳遞類神經網路模擬之研究學習速率在倒傳遞類神經網路模擬之研究〔碩士論文,亞洲大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0118-0807200916282985

延伸閱讀