針對控制系統以網路做為通訊媒介的環境,本文提出一個自動增益補償的模糊增益調節器(Fuzzy Gain Tuner, FGT)來因應網路隨機的延遲量,所造成網路控制系統不穩定甚至不可控制的響應結果。而此FGT以網路傳輸一趟所花費的時間(Round-trip time, RTT)做為網路延遲狀況的輸入,利用RTT可以分析出網路的壅塞及變動情形;另外FGT的模糊法則可以透過離線狀況下建立各種網路延遲的系統模型,再交由基因演算法(Genetic Algorithm, GA)應用於Fuzzy Takagi-Sugeno-Kang (TSK) Model學習,以得到在不同延遲條件下最佳的控制系統效能。最後,本文以自動導航車做為受控平台進行路徑追隨與尋標避障等實驗,說明本模糊增益調節器在實際系統中的可行性。
Aim at the control system that communication by network system, this thesis proposes a “Fuzzy Gain Tuner, FGT” that can deal with the random delay of the network to cause an unstable and even not controllable result. The FGT considering the network delay status by the round-trip time (RTT) of network transmits a round-trip. Utilize RTT to analyze the congestion and the variation of the network delay. In addition, the fuzzy rules of FGT can learning automatically by genetic algorithm (GA) and the Takagi-Sugeno-Kang model (TSK) that considering many network delay models to get the better performance under difference delay conditions. Finally, experiment of path following and obstacle avoidance by the automatic guided vehicle (AGV) will prove the FGT feasibility in the practice control system.