基于神经网络预测控制的锅炉过热汽温控制研究-控制理论与控制工程专业论文.docxVIP

Subject ：Research of Boiler Superheated Steam Temperature Control Based on Neural Network Predictive Control Specialty ：Control Theory and Control Engineering Name ：TanYuanfei （Signature） Instructor：Wang Zaiying （Signature） ABSTRACT The superheated steam temperature control is one of the most important tasks in automatic control system in thermal power plants. The superheated steam temperature directly affects the safe and economic running of thermal power plants. While the traditional PID algorithm is mainly used in the process. And its effect is bad. So research of boiler superheated steam temperature control is very significance This article analyzes the static and dynamic characteristics of the boiler superheated steam temperature system. And compares the advantages and disadvantages of double-loop control with a differentiation and cascade control based on the PID . Analyzes the cause of that the traditional predictive control is difficult to apply in the boiler superheated steam temperature system. So proposed a neural network predictive control algorithm that use neural network as prediction model on the basis of the traditional predictive control. It takes full advantage of the capabilities of the neural network in nonlinear mapping approximation and the actual optimal control of receding-horizon in predictive control. And with an online real-time correction capability. In addition, this article using a maximum error judgment algorithm in the link of online correction to reduces the computation. Quantitative analyzes the main parameters of the neural network predictive controller and determine the effect from each parameter to controller. Finally, use the neural network predictive control algorithm into the boiler superheated steam temperature control system , and compare the control performance of the neural network predictive control and traditional PID in attemperating water disturbance, flue gas disturbance and load disturbance. Simulate in Matlab ,