多变量PID型神经元网络控制系统在再热蒸汽温度控制上的仿真

THE CONTROL SYSTEM OF MULTI-VARIABLE PID NEURON NETWORK AND ITS APPLICATION IN REHEATED STEAM TEMPERATURE CONTROL

融合解耦控制理论与神经元网络控制原理,给出了一种多变量的PID型神经网络控制方法。应用所给出的控制算法,对火电厂再热蒸汽温度、低温过热器出口蒸汽温度控制进行了仿真。仿真结果表明,控制算法对再热蒸汽温度控制具有良好的解耦性能和自学习控制特性,当被控对象参数变化时系统具有较强的鲁棒性。

A control system of multi- variable PID neuron network has been given by merging the decoupling control theory with the neuron network principle, and the limitations of PID decoupling control in multi- variable control system and the feasibility of introducing the neuron network control system being analysed. A simulation test of temperature control for reheated steam and for outlet steam from the low - temperature superheater has been carried out by using the given control algorithm. Results of simulation show that the said control algorithm has better decoupling performance and self - learning control property for the reheated steam temperature control, and the system has stronger robust in the event of parameters variation concerning the controlled object.