Simulation Research On The Coordinated Control System Of Unit Heat-Engine Plant Unit

In this paper,the coordinated control system of unit heat-engine plant unit is the research core.A series of problems in the coordinated control system are analysed.When simplifies the turbine-generator unit as a two inputs and two outputs control and make some reasonable hypothesis,this paper sets up a dynamic math model of the Coordinated Control System.Firstly,this paper analyzes the coordination system of boiler controller,which is often the existence of a certain delay,and adopting conventional PID control in the process can not get good results,so the fuzzy predictive control algorithm is introduced to the boiler side.The fuzzy predict strategy successfully predict the value of the main parameters and changing trends in the future by computing them and their changing tendency that have occurred in the system.The simulation results have shown the system overshot can be thus be effectively reduced.The main task of CCS is to satisfy the load instruction requirement of the electric network,to reduce disturbances in different forms,and to ensure the stability of the unit at the same time.Instead of one-degree-of-freedom PID controller is adopted as the main controller of the turbine,and the later can somewhat reduce the dependency of CCS on the feed forward loop of the boiler.The unit of the boiler and steam turbine is the strong-coupling system in order to achieve a single one-on-one control,decided to adopt a neural network decoupling control of many variables.Simulation results shows to achieve a good decoupling effect.This paper introduces the Neural Net,Fuzzy self-adaptive control into CCS control system.And an intelligent PID control system based on Neural Network,Fuzzy control is composed.Through simulation and robust analysis for the boiler plant of a coordinated control system,the paper illuminates the vast foreground of this method for controlling complicated industrial processes.Compared with traditional PID controller,this intelligent control algorithm improved the response rate of the load and the control performance of the system,and achieved better control effect.