智慧型汽車或輪式機器人將在各種不同場所取代人們，面對各種不同的事情，現在我們已經變成了自動化操作，因此，它將能夠減少人力的需求及數量，只需要透過定期維護和故障排除。未來智慧型汽車將具備更多的可變性，然而智慧型汽車的追蹤系統就顯得非常重要，沒有一種追蹤器可以廣泛適應變化環境的現實生活。針對不同追蹤器的多種方法，在追蹤過程中，根據不同的環境，會出現比較好，特別容易出現故障的情況。然而，存在一些缺點，例如機構的硬度和磨損。為了解決這些問題，近年來已經進行了許多研究以應用該領域的各種方法。
本論文設計了一種以倒傳遞模糊控制器，用於電動汽車防撞系統，在控制器中，模糊滑動面被用作輸入語言參數。首先建立模糊滑動面，然後用倒傳遞規律對輸出隸屬度函數值進行調整。
為了驗證所提出方法的有效性，本文利用Matlab進行了仿真研究，並分別對汽車機器人平台進行了實驗。從模擬和實驗結果來看，智慧型汽車具有良好的即時追蹤能力。
Smart cars or wheeled robots will replace people in various places and face a variety of different things. Now that we have become automated, we will be able to reduce manpower demand and quantity, only through regular maintenance and troubleshooting. . In the future, smart cars will have more variability, but the tracking system of smart cars is very important. There is no tracker that can be widely adapted to all equipment in the world. A variety of methods for different trackers will appear better in the tracking process depending on the environment, and are particularly prone to failure. However, there are some disadvantages such as the hardness and wear of the mechanism. In order to solve these problems, many studies have been conducted in recent years to apply various methods in the field.
In this dissertation, an inverse pass fuzzy controller is designed to be used in collision avoidance system of electric vehicles. In the controller, the fuzzy sliding surface is used as the input language parameter. First, the fuzzy sliding surface is established, and then the output membership function value is adjusted by the inverse transfer law.
In order to verify the effectiveness of the proposed method, the simulation study was carried out using Matlab, and experiments were performed on the autobot platform. From the simulation and experimental results, the smart car has a good real-time tracking capability.
