基于炼油过程的克服纯滞后的广义预测控制

The Generalized Predictive Control for Overcoming the Promblem of Pure Lag System Based on the Process of Refining

针对炼油工业过程中存在的纯滞后问题,提出一种克服纯滞后的广义预测控制方法。由神经网络辨识出非线性系统的纯滞后时间参数,在每个控制周期内,递推预测非线性滞后系统在未来时刻的工作点,在工作点附近对非线性系统进行线性化,根据得出的线性化模型进行广义预测控制,预测出未来对应时刻的系统输出,从而达到预期的控制目的,仿真结果表明,此方法能快速有效地跟踪系统给定值,控制效果良好。

This paper focused on extending the generalized predictive control algorithm for overcoming the promblem of pure lag system based on the process of refinng. First non-linear system identified pure lag time parameters by the neural network, then at each control period, we predict the nonlinear system＇s future working point at which we linearize the nonlinear system and get a linear system, then we apply the generalized predictive control algorithm to this linear model to control the nonlinear system and predict the system future output and achieve the desired objective.The simulating results show that this method can track the set value of the system rapidly and efficiently,and has a good control result.