基于模糊PID算法的智能车电机转速控制研究

针对传统PID控制参数难以适应不同曲率半径车道下智能车运行速度变化和RS-540有刷直流伺服电机调速变化的问题,设计了自适应模糊PID算法。首先,建立了电机的数学模型,提高控制精度,在此基础上构建了自适应模糊PID控制器,然后,通过PWM脉冲改变电枢电压的平均值来控制电机转速,再通过低通滤波使速度输出平滑。加入陀螺仪使电机在车道缺线的情况下保持原来的转速,并通过Simulink对电机进行仿真。实验测试表明,模糊PID控制能够较好地控制电机的转速,使智能车沿着车道稳定快速地运行。

Research on Motor Speed Control of Intelligent Vehicle Based on Fuzzy PID Algorithm

In order to solve the problem that the traditional PID control parameters are difficult to adapt to the speed change of the intelligent vehicle and the speed change of the RS-540 brush-DC servo motor in the lane with different curvature radius,an adaptive fuzzy PID algorithm is designed.First,the mathematical model of the motor is established to improve the control accuracy.On this basis,an adaptive fuzzy PID controller is built.Then,the motor speed is controlled by changing the average value of armature voltage with PWM pulse,and the speed output is smoothed by low-pass filtering.The gyroscope is added to make the motor keep the original speed in the case of lane lack of line,and the motor is simulated by Simulink.The experimental test shows that the fuzzy PID control can better control the motor speed,so that the intelligent car can run steadily and rapidly along the lane.