基于遗传算法优化的双回路模糊控制倒立摆系统

通过遗传算法、模糊控制、PID的结合,对直线一级倒立摆的平衡控制问题进行了优化控制。首先用牛顿-欧拉法建立倒立摆的动力学模型,得出系统的传递函数和状态空间表达式,分析系统的稳定性和可控性。以此为基础,先设计了PID单回路和双回路控制器;然后用遗传算法优化PID参数;再用优化的参数设计双回路模糊PID控制器;并用MATLAB对系统进行了仿真。纵向和横向控制方法的对比分析表明:该方案控制效果最好,能同时控制角度和位移;其参数可在最优PID初值的基础上在线修改,实现最佳调整,使对象具有良好的静态和动态性能。

Dual loop fuzzy control inverted pendulum systembased on genetic algorithm optimization

Through the combination of genetic algorithm, fuzzy control and PID, the balance control problem of the linear inverted pendulum is optimized. Firstly, the dynamic model of the inverted pendulum is established by Newton-Euler method, and the transfer function and state space representation of the system are obtained. The stability and controllability of the system are analyzed. On this basis, the PID single loop and dual loop controller is designed firstly, then the PID parameters are optimized by genetic algorithm, and then the fuzzy dual loop PID controller is designed with the optimized parameters, and the system is simulated by MATLAB. Comparative analysis of longitudinal and lateral control method show that the control effect is best, can also control the angle and the displacement parameters based on optimal PID initial online modification to achieve the best adjustment, the object has good static and dynamic performance.