本論文提出一車型機器人的動態模型並設計四種控制器，包含模糊停車控制器，滑動模式動態控制器、適應性滑動模式動態控制器及適應性模糊滑動模式動態控制器，以完成自動停車或軌跡追隨的任務。模糊停車控制器能有效地讓車型機器人停到它所偵測出的停車格當中，其餘三個動態控制器也都能讓車型機器人達成軌跡追隨的任務並驗證所提出之車型動態模型的可行性及有效性。模糊停車控制器係整合超音波感測器所偵測到的環境資訊及搭配雙耳法定位功能，使車型機器人能辨識出停車格與障礙物位置，並避障以保證停車的安全性。接著為了確保車型機器人的穩定性，本論文藉由李亞普諾夫穩定性理論，證明基於車型機器人動態模型所提之三個動態控制器在系統參數不確定及外部擾動的影響下，仍能完成軌跡追隨之目的。最後，實驗結果證實模糊停車控制器可有效地執行停車任務，而電腦模擬結果顯示所設計之動態控制器可有效地控制車型機器人完成軌跡追隨之任務。

This dissertation proposes a dynamic model of car-like mobile robot (CLMR) and presents four dynamic controllers, which including the fuzzy parking controller, sliding-mode dynamic controller, adaptive sliding-mode dynamic controller, and adaptive fuzzy sliding-mode dynamic controller. The controllers are utilized to accomplish the parking or trajectory tracking missions. The fuzzy parking controller can make the CLMR to park effectively in the detected parking space, and the other three dynamic controllers can perform the trajectory tracking task and verify the availability of proposed CLMR dynamic model. By integrating the obtained surrounding information of the robot from ultrasonic sensor data and adopting the binaural approach, the CLMR can recognize the parking space and obstacle position in the experimental environments. Additionally, the fuzzy parking controller can ensure the ability of the CLMR to withstand collision in order to guarantee safe parking. Furthermore, base on the proposed dynamic model of CLMR, the three dynamic controllers are presented to reduce the effect of the external disturbances and system uncertainties of the CLMR, and to accomplish the trajectory tracking task. This dissertation also proves the stability of the CLMR with these three dynamic controllers by the Lyapunov stability theory. Finally, the practical experiments demonstrate that the proposed fuzzy parking controller is feasible and effective and the simulation results validate the effectiveness of the three proposed dynamic controllers.

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