本論文設計實現一台以CompactRIO為主控制平台的二輪機器人，並且以圖形化程式語言LabVIEW設計程式來讓二輪機器人可以自我平衡。CompactRIO包括一組即時處理器、FPGA的可重設晶片、類比與數位的I/O，其可以透過LabVIEW來進行程式設計。CompactRIO的I/O埠整合了兩個感測器的訊號，分別為一個單軸陀螺儀(Gyro)及一個三軸加速度計(Accelerometer)所量測二輪機器人的傾斜角速度及傾斜角度，再使用卡爾曼濾波器(Kalman Filter)來取得較正確的傾斜角度。本論文設計實現一個二輸入一輸出的模糊控制器來讓二輪機器人可以平衡控制，其以卡爾曼濾波器所估計出的角度與角度變化量作為模糊控制器的輸入，並且以模糊控制器的輸出值作為直流馬達的控制。由實驗結果可知，本論文以LabVIEW圖形化程式與CompactRIO主控制平台所設計實現的模糊平衡控制器確實能讓二輪機器人可以自我平衡，並在受到外力干擾後也可以迅速恢復平衡狀態。 In the thesis, the graphical programming language LabVIEW and the embedded system platform CompactRIO are used to design a two-wheeled self-balancing robot. CompactRIO is an embedded integrated controller including real-time processor, reconfigurable FPGA-based chip, I/O of analog and digital. The signals of two sensors are used to be inputs of CompactRIO. One is an one-axle gyro and the one is a three-axle accelerometer. They are used to measure the tilt angle and angular velocity of the two-wheeled robot. The Kalman filter is used to improve the measurement errors caused by the gyro and accelerometer so that a correct tilt angle can be obtained. A two-input and one-output fuzzy controller is design to balancing control the two-wheeled robot. The tilt angle obtained by the Kalman filter and the increment value of angle are used to be two inputs of fuzzy controller, and the motor speed is the output of fuzzy controller. From some experiment results, we can see that the implemented fuzzy controller actually let the two-wheeled robot balance by itself. And the robot quickly becomes a balancing state when it has an outside small force.
