Single tank liquid level control based on improved BP neural network PID control algorithm

By analyzing the structure of single tank liquid level control system and the corresponding mathematical model, the system simulation model of a single tank liquid level control system is firstly established. Secondly, the theory of conventional BP neural network PID control algorithm is introduced. Thirdly, an improved learning rate technology is proposed to solve the slow convergence problem of traditional method. Finally, simulation results are provided to indicate that this improved method has the advantage of quick velocity response, less overshoot, higher control precision and good robustness in comparison with traditional BP-PID control algorithm.