Optimization Research On Parts Of Thermal Process Control System In Anshan Iron And Steel Group Corporation's Second Power Plant

This thesis aims at doing a reaearch to optimize the parts of anshan iron and steel's second power plant thermal process control system , under the guidance of the advanced control theory, do the following research work.The power plant control process mainly use the multi-loop PID controllers.accurate calculation on the Multi-loop controller parameters in the stability region is the very important parts to achieve precise thermal control processes, Conventional method is difficult to accurately calculate the multi-loop PID controller parameters of the stability region,so we convert to calculate the linear matrix inequalities with robust stability criteria instead,thus combined the modeling methods with the linear parameters related to lyapunov function,discussed one kinds of the solving multi-loop controller parameters methods-LMI.the results shows that use the LMI to calculate the calculate the stability region of parameters is feasible.As the problem exist,that the uneven heating on the heated body,the delay of the main steam temperature,nonlinear and time-varying during the temperature control system,the theies do a research on which can even heated. And design a simple and practical high-precision observer,which using neural network and fuzzy control technolog to achieve the temperature reconstruction,feedforward control and effective control.There always exists the characteristics of the main steam pressure system controlled objects were complex(nonlinear,strong coupling, large delay, operating conditions change frequently).the theise consider to combine the fuzzy control, robust control parameter optimization algorithm with the traditional PID control techniques.then proposed the new strategies based on the parameter self-tuning and the FUZZY-PID controlled main steam preesure boiler. Application results show that using this control strategy can significantly improve the quality of the system of control and effectively overcome the adverse effects on the changes in working conditions.