【作者】 牛立尚；

【导师】 张树功；

【作者基本信息】 吉林大学 ， 计算数学， 2007， 硕士

【摘要】 预测控制是近几十年来飞速发展,并取得广泛应用的控制方法.预测控制方法的一个重要优点是它能够处理操作变量和状态的约束,目前已被广泛应用于石油化工及相关工业.在工业过程中,满足约束是非常重要的,因为经济效益要求控制作用和状态接近其所允许的边界.因此,设计一种好的预测控制方法无论在理论方面还是应用方面都具有重要的意义.本文主要针对多输入输出系统研究了预测控制方法,主要内容包括:(一)系统地回顾了预测控制的发展历史,并对具有代表性的几种预测控制方法进行了简要的介绍和分析.(二)对输出终端带不等式约束情形的多输入多输出广义预测控制系统,提出了通过修改输入柔化系数而使约束得以满足的方法.(三)针对多输入多输出多变量耦合系统,根据动态矩阵控制模型通过矩阵分解对其进行上三角解耦.更多还原

【Abstract】 Predictive control is a kind of advanced control technologies that is based on the model of plants, so it is also called model predictive control. It is a novel computer control algorithm first appeared in industrial area in Europe and America in 1970s.French researcher Richalet et al first proposed the conception, background, mechanism and performance of the model predictive heuristic control. Then the theory of model predictive control was further developed by Mehra, Culter and Clark et al. In 1980s, model predictive control received extensive attention of the western researchers for its distinct merits and features and it has been deeply studied from different aspects with many mathematic methods.Predictive control is a form of control that developed rapidly and gained extensive application in recent years. Predictive control is a kind of advanced control technology, which is based on the model of plants. The model predictive control was straightly engendered and sophisticed from the applications of industrial process. Model predictive control requires low accuracy of model precision, but it can provide high performance.Predictive control’s current control action is obtained by solving at each sampling instant, a finite horizon open-loop optimal control problem, using the current state of the plant as initial state, the optimization yields an optimal control sequence and the first control in this sequence is applied to the plant. An important advantage of this type of control is its ability to cope with hard constraints on controls and states. It has, therefore, been widely applied in petro-chemical and related industries where satisfaction of constraints is particularly important because efficiency demands operating points on or close to the boundary of the set of admissible states and controls。 Model predictive control is a quite effective optimal control algorithm, which made up the deficiency of modern model theory in complex plants. In the recent years, with the development of many kinds of the control theory, such as intelligent control, PID control, wavelet theory, robust control and hybrid systems control, the theory of model predictive control has also obtained rapid developments.Based on the study of model predictive control and the new requirements from the practice industrial processes for the theory of model predictive control, some desiderated problems for the theory of model predictive control, corresponding results are given. The main contents of this thesis are stated as follows:1) It completely reviewed the development of model predictive control and introduced and analyzed the main types of model predictive control,included Dynamic Matrix Control, Model Algorithm Control, and Generalized Predictive Control in the literature.2) we study the problem of constrained Generalized Predictive Control of MIMO system. We assume that the outputs satisfy some inequality constraints and solve the constrained problem by choosing suitable adjustable coefficientλ. To this end, we estimate parameters through the known data instead of the computation of the inverse matrix.3) Based on the DMC algorithm a decoupling design method of multi-variable system is presented. In the paper, the system is deposed with one to much upper triangular decoupling method, not with one to one diagonal decoupling method. So the decoupling problem is done step by step. The simulation of the decoupling algorithm is good.The conclusion and perspective are given in the end of the paper.更多还原