Intelligent Systems to the Control of a Mobile Vehicle

• Main Authors: Yan-lu Chang, 張晏祿
• Other Authors: Chun-shien Li
• Format: Others
• Language: zh-TW
• Online Access: http://ndltd.ncl.edu.tw/handle/43773330016331499041

碩士 === 國立臺南大學 === 機電系統工程研究所碩士班 === 97 === This study is focused on motion control of the electric mobile vehicle using Neural-net-based Fuzzy logic System (NFS). The DC motor for driving the front wheel of the vehicle whose angular direction will affect the movement of the vehicle . The dynamic behaviors governing equation of the DC motor and the mobile vehicle are derived in the study. The computer simulation for the control study using the governing equation are conducted using MATLAB. The target angle for turning the front wheels can be obtained according to the road condition , which is dependent on the curve of the road. The NFS controllers are used to calculate the input voltage of the motor to turn the vehicle respectively. Using the difference between the output angle of the vehicle and the target angle, the NFS controllers can adjust the angle until the vehicle reaches the goal. The NFS controllers must be trained before they can be used. The well-known Random Optimization (RO) machine learning method is used in the study. The NFS controllers are designed using fuzzy logic and neural network . The error, error derivative and error integral signals are used on the inputs to the NFS. The experimental results show good performance.