主蒸汽温度的BP神经网络PID控制系统的研究

Research on BP Neural Network PID Control System for Main Steam Temperature

针对火电厂主蒸汽温度系统大惯性、大迟延、非线性的特点,常规串级PID控制难以取得满意的调节效果,为了改善常规PID控制的不足,文章在研究BP神经网络的基础上,把BP神经网络PID控制应用到主汽温控制系统中。运用matlab仿真,结果表明,与传统控制相比BP神经网络PID控制算法有效减小了系统的超调量,提高了系统的响应速度,在主汽温控制系统中具有很好的控制效果。

Aiming at main steam temperature system of the thermal power plant with the characteristics of large inertia,non-linearity and large time delay,the conventional cascade PID control is difficult to obtain satisfactory control effect.In order to improve the effect of conventional PID,the BP Neural Network PID control system is used in the main steam temperature control system.The simulation result indicates that the BP Neural Network PID control algorithm has good control quality,small over shot and improves the response speed of control system.So the control method proposed is an effective control strategy for the main steam temperature system.