本論文以SOPC (System on a Programmable Chip)技術設計實現一個兩輸入一輸出的模糊控制器來讓兩輪機器人可以自我平衡，並且於受到干擾後可立即恢復到平衡狀態。機器人底盤左右的兩個輪子分別由直流馬達來控制機器人的移動，機器人的主要控制核心為一個NIOS II開發板，其負責所有訊號的擷取與馬達的控制。在訊號的擷取上，本論文採用一個單軸陀螺儀(Gyro)以及一個三軸加速度計(Accelerometer)來量測二輪機器人的傾斜角速度以及傾斜角度。此外，本論文使用卡爾曼濾波器(Kalman Filter)來有效改善陀螺儀與加速度計在量測傾斜角度時所產生的誤差，讓二輪機器人獲得一個正確的傾斜角度。在模糊控制器的設計上，本論文採用卡爾曼濾波器所得到之傾斜角度以及陀螺儀所計算出之傾斜角速度為輸入，而馬達速度控制命令為輸出，並且由SOPC所實現的PWM訊號來控制兩個直流馬達的轉動，讓二輪機器人可以保持平衡的姿態。從實驗的結果可知，本論文所設計實現的模糊控制器確實可以讓兩輪機器人自我平衡，並且在受到外力干擾後亦可以快速恢復到平衡狀態。 In this thesis, a two-input-one-output fuzzy controller is design and implemented based on the SOPC (System on a Programmable Chip) technique to let the implemented two-wheeled robot can balance by itself and let the robot reinstate the balancing state quickly when some output perturbation is produced. The chassis of robot has two wheels which are controlled by two DC motors and the control board of robot is a Nios II development board which processes all the signal and motor control. In the signal process, an one-axle gyro and a three-axle accelerometer are used to measure the tilt angle and angle velocity of robot. Furthermore, 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. The tilt angle measured by the Kalman filter and the angle velocity measured by the gyro are used to be two inputs of fuzzy controller, and the motor speed is the output of fuzzy controller. The PWM signal based on the SOPC technique is realized to control two DC motors. From some experiment results, we can see that the implemented fuzzy controller actually let the two-wheeled robot balance by itself.
