在講求時效的現代，隧道內營建機械手臂的自動化，取代人工量測及操作，無疑是最快速簡捷的方式，所以本研究主要以小型的隧道內營機械手臂作做為分析，模擬機械手臂在隧道中的工作環境，達到有效的定位控制。本論文初步採用模糊控制器來定位，為了配合即時控制的需求及改善控制曲線，論文進一步則是結合灰色預測及模糊控制來預測機械手臂的位置，並且於上升時間(rise time)及超越量(overshoot) 等控制係數作一比較，從中可知此方法能使機械手臂達到更理想的定位輸出。 除此之外，為能掌握隧道內的情況，我們的機械手臂亦結合超音波做隧道面的掃描，將超音波的感應值做轉換，控制隧道手臂的伸縮，達到偵測的目的。 綜合以上實驗，我們發現在大部分的實驗中，機械手臂均可達到預期目標，本論文將在最後探討小部份結果不甚理想的原因，並提出未來改進的方向。 In this study, we propose a new model to combine with fuzzy control and grey predictor to improve the output response that only use fuzzy theorem to manipulate the robotic motion control. Actually, if we only use the fuzzy controller to control the system, the system factor of system performance such as the rising time and the overshoot were not the desired. In general, the rising time and the overshoot are the important indices of the system response. However, most of controllers can not improve the overshoot and the rising time at the same time. Here, we propose a new technique that can prevent the system response from exceeding the set point and adjust the rising time by using the sampling interval of data sequence"n". The idea is employed to the control of a three-axis robot. The experimental results show that the proposed controller not only drastically reduce the overshoot, but also maintain a small extent of the settling time and the steady state error.
