基于模糊神经网络PID算法的液位控制系统研究

在工业生产中，液位控制系统得到了广泛应用，但是对于这种大滞后、非线性的复杂控制系统，传统的PID控制方法存在着参数整定困难，控制效果不理想的缺陷。在对传统的PID算法、模糊控制算法和神经网络算法研究的基础上，提出了一种将模糊神经网络PID算法应用到液位控制系统中去的解决方案，并采用MATLAB对液位对象控制进行仿真实验，同时采用A3000型水箱实验平台对仿真实验结果进行验证。研究结果表明，基于模糊神经网络的PID算法的液位控制系统在调整时间和超调量上都优于传统的PID算法，控制效果和抗干扰能力更强，克服了传统PID算法的不足。

Research of liquid level control system based on fuzzy neural network PID algorithm

In industrial production, liquid level control system has been widely used, but for this complex control system with large delay and non-linearity, the traditional PID control method has the drawbacks of difficult parameter tuning and unsatisfactory control effect. Based on the research of traditional PID algorithm, fuzzy control algorithm and neural network algorithm, this paper puts forward a solution of applying fuzzy neural network PID algorithm to liquid level control system. Matlab is used to simulate the control of liquid level object, and A3000 water tank experimental platform is used to verify the simulation results. The results show that the liquid level control system based on the PID algorithm of the fuzzy neural network is superior to the traditional PID algorithm in adjusting time and overshoot, and has better control effect and anti-interference ability, which overcomes the shortcomings of the traditional PID algorithm.