基于不同建模周期的多变量预测控制研究

文中对各通道特性差异比较大的多变量系统采用了不同建模周期的预测建模方法及预测控制算法，并给出了算法推导和仿真实例。     

新型多变量有约束预测控制器

针对一类多变量系统给出了带约束输入的GPC算法，该算法充分考虑了控制输入及其增量均受约束的情况，而且不必求Diophantine方程，大大减小了计算量；仿真结果说明该算法对多变量系统具有良好的鲁棒性和跟踪性能。     

多变量协调自适应控制器初步研究

本文初步研究了多变时过程控制器设计的优化目标和约束的统一表达体系,将模块多变量控制技术引入自适应控制器的设计过程,提出了多变量协调自适应控制器的概念,并初步解决了有约束的多目标优化控制的设计问题。     

定量水分预测函数多变量控制的研究

造纸工业抄纸过程中,定量和水分的控制品质直接影响纸张的质量.针对其中存在的大时滞、大惯性以及强耦合的特点,提出了基于一阶加纯滞后对象的多变量预测函数控制算法.通过优化多变量性能指标求得控制律,并参考Smith预估思想对滞后时间进行补偿.定量水分系统的仿真结果说明了该算法能较好地达到控制性能的要求,并具有良好的鲁棒性.     

基于模糊PI控制器的永磁同步电机矢量控制仿真研究

为改进传统PID控制的永磁同步电动机调速系统性能,提出一种基于模糊PI控制的永磁同步电机矢量控制新方法.仿真结果表明该方法控制精度高,动态特性好,适合于永磁同步电机的速度控制.     

PI控制器在生产控制中的应用研究

以制造系统加工过程的在制品为研究对象,将比例积分PI(proportional and integral)控制算法应用于生产过程的控制,建立了PI控制的级联控制模型,同时将PI控制器参数的设计问题转化为优化问题;并以发动机曲轴箱体生产线为例,进行了PI控制器的实例化设计.     

多变量预测控制技术在抽余液塔中的应用

芳烃是石油化工生产中重要的基础原斟．近几十年来发展非常迅速。芳烃生产主要由重整，抽提、歧化、吸附分离、异构化等过程组成．芳烃抽提是其中的重要组成部分。芳烃抽提联合生产装置中的抽余液塔存在进料波动大、操作变量多．关联性强、容量滞后大等特点．是典型的难以控制的多变量过程；正因为如此．在工业生产中该塔的     

一种输入输出维数不等的多变量自校正补偿控制

本文给出了一种输入输出维数不相等的多变量自校正控制,并考虑了自校正控制中存 建模误差的问题,得出了模型误差补偿的多变量自校正控制。仿真结果表明了这种算法的有效性。     

模糊预测控制在水泥生产过程中的应用

介绍一种新型预测控制算法——模糊预测控制(FPC)在水泥回转窑分解炉出口温度控制中的应用。应用结果表明，引入模糊预测控制后，系统的控制效果明显优于PID。与简单的模糊控制相比，系统的稳定性也有所提高。     

基于多变量灰色模型的磨削参数预测研究

磨削参数影响混凝土的金刚石磨削应用效果.利用实验数据样本,基于多变量灰色预测理论建立了混凝土的金刚石磨削参数灰色预测模型.结合实验数据分析和验证了以磨削混凝土的金刚石磨削参数为输入、以磨削加工量和金刚石磨粒磨损为输出的预测模型,实例结果表明,该模型可以较好地预测金刚石刀具的机械加工量和磨粒磨损值.     

多变量非自衡系统的预测控制研究

该文研究了多变量非自衡对象的特点及控制问题，推导了一种适用于非自衡系统的多变量预测控制算法，通过对环境试验设备温度湿度控制系统的仿真实验，证实了此算法的有效性和实用性。     

An approach to predictive control of multivariable time-delayed plant: stability and design issues

In this paper, a new method of multivariable predictive control is presented. The main advantage of a predictive approach is that multivariable plants with time delays can be easily handled. The proposed control algorithm also introduces a compact and simple design in the case of higher-order and nonminimal phase plants, but it is limited to open-loop stable plants. The algorithm of the proposed multivariable predictive control is developed, designed, and implemented on an air-conditioned system. The stability of the proposed control law is discussed.     

Centralized PI control for high dimensional multivariable systems based on equivalent transfer function

This article presents a new scheme to design full matrix controller for high dimensional multivariable processes based on equivalent transfer function (ETF). Differing from existing ETF method, the proposed ETF is derived directly by exploiting the relationship between the equivalent closed-loop transfer function and the inverse of open-loop transfer function. Based on the obtained ETF, the full matrix controller is designed utilizing the existing PI tuning rules. The new proposed ETF model can more accurately represent the original processes. Furthermore, the full matrix centralized controller design method proposed in this paper is applicable to high dimensional multivariable systems with satisfactory performance. Comparison with other multivariable controllers shows that the designed ETF based controller is superior with respect to design-complexity and obtained performance.     

Improved fuzzy PID controller design using predictive functional control structure

In conventional PID scheme, the ensemble control performance may be unsatisfactory due to limited degrees of freedom under various kinds of uncertainty. To overcome this disadvantage, a novel PID control method that inherits the advantages of fuzzy PID control and the predictive functional control (PFC) is presented and further verified on the temperature model of a coke furnace. Based on the framework of PFC, the prediction of the future process behavior is first obtained using the current process input signal. Then, the fuzzy PID control based on the multi-step prediction is introduced to acquire the optimal control law. Finally, the case study on a temperature model of a coke furnace shows the effectiveness of the fuzzy PID control scheme when compared with conventional PID control and fuzzy self-adaptive PID control.     

Auto-tuning of PID controller parameters with supervised receding horizon optimization

In this paper, a novel two-layer online auto-tuning algorithm is presented for a nonlinear time-varying system. The lower layer consists of a conventional proportional-integral-derivative (PID) controller and a plant process, while the upper layer is composed of identification and tuning modules. The purpose of the upper layer is to find a set of optimal PID parameters for the lower layer via an online receding horizon optimization approach, which result in a time-varying PID controller. Through mathematical analysis, the proposed system performance is equivalent to that of a standard generalized predictive control. Simulation and experiment demonstrate that the new method has a better control system performance compared with conventional PID controllers.     

基于陶瓷窑炉温控的模糊预测控制系统的应用

针对陶瓷窑炉热容量大、滞后量大、非线性等特点,提出了一种将模糊控制与预测控制相结合的控制算法,增强了算法的跟踪与抗干扰能力。仿真结果表明,这种方法与传统的PID控制相比,具有较高的稳态精度和动态特性。     

Considerations for multivariable control of the twin-roller strip caster

Twin-roller steel strip casters may offer advantages with respect to classical continuous casting hot rolling processes. Some works have reported control aspects of this process, however, the cross coupling elements have not been evaluated. In this work, the derivation of a 3 x 3 linearized multivariable model for process control purposes proposed in previous investigations is presented. The model was simplified to a 2 x 2 plant. The purpose of this work is to show that the process is highly interactive by performing an analysis of its multivariable characteristics. Some important considerations for process control design based on such multivariable characteristics of the process are discussed.