Generalized Predictive Control Of The Boiler Combustion System

Industrial boiler plays an important role in our national economy, and it isalso an important power facilities. In recent years, with the continuousenhancement of the energy-saving and environmental awareness, the problem ofthe optimization of boiler production process control and real-time monitoringhas become the control, energy and environmental protection research focus. Thispaper analyzes the industrial boiler combustion process with multi-input,multiple-output, large time delay, nonlinear and strong coupling features, and onthe base of the full study and learn the basic principles of generalized predictivecontrol, advanced a new algorithm that is to avoid the inverse matrix of themultivariate implicit generalized predictive control, then reducing the storagetime, expanding the range of options of the forecast domain and control oftime-domain at the same time.Generalized predictive control algorithm is a strong robustness of intelligentcontrol algorithms developed in recent years. Because it does not depend on aprecise mathematical model, therefore, it is apply to the complex industrial boilercombustion control system. But the algorithm is computationally expensive, needto be online repeatedly calculating the inverse matrix, greatly limits the choice ofcontrol horizon, but also takes up a lot of memory, although the domestic andforeign scholars have put forth many new and improved algorithm, but most ofthem need to get reverse matrix. This chapter gives a non-inverse generalizedpredictive control and multi-variable implicit generalized predictive control of acombination of control methods, not only reduced the storage time, but alsoincreased the range of options of the forecast and control domain, improve thecontrol stability of the system.Boiler’s combustion process is complex, and it have many control variables, and there is a strong coupling between these variables, there are no small role inthe interference of the realization of the ideal control.To select one or several keyparameters from these variables and measure them more exactly are required forideal control. In this paper, advanced soft measurement technology that is softsensor technology to measure the key parameters of the system, also providesstrong support for the reliability of the new algorithm.Finally, in this paper has further discussed the development of GPC, and itsbroad space for development and application prospects.