过程控制系统综合性实验设计与教学实践

将分散的过程控制课内实验,按其内在联系与顺序进行内容的串联与综合,将Matlab仿真引入过程控制系统实物装置实验,以实测得到的实验对象模型为仿真原型,按照控制系统装置的实际情况构建Simulink仿真模型进行Matlab仿真,再用仿真得到的控制参数选取实验参数。设计的实验包括模型测试、简单系统实验和复杂系统实验,实验手段采用Matlab仿真与实物实验相结合的综合性实验,以提高实验效率与教学效果。以液位串级控制系统综合性实验教学实例,阐述了实验教学方法。     

New predictive control algorithms based on Least Squares Support Vector Machines

INTRODUCTION Model predictive control (MPC), based on pre-dictive model and receding horizon optimization, has become an attractive feedback control strategy, be-cause it has found successful applications, especially in the process industry. For this kind of control strategy, the predictive model is a crucial component because the essence of MPC is to optimize the fore-cast of process behavior (Rawlings, 2000), and the forecast is accomplished with the predictive model. If the controll…     

Predictive control of a class of bilinear systems based on global off-line models

INTRODUCTION Bilinear systems are a kind of important nonlinear systems with relatively simple structure, and many industrial processes can be described as a bilinear system. Thus research on the control of this kind of systems is very important. On the other hand, model predictive control (MPC) (Clarke et al., 1987) has been widely used in industrial applications and many predictive control methods focusing on bilinear systems are emerging (Bloemen et al., 2001; Fontes et al., 2004; He…     

水文预报的时间序列神经网络模型

时间序列分析在水文预报中起重要作用 ,其关键是要建立一个合适的预报模型 .文章提出基于 BP算法的单输出和多输出水文预报时间序列神经网络模型 ,克服了以往多种基于随机分析预报模型的缺点 ,不仅能实现快速灵活的信息处理 ,而且具有很强的非线性映射和自学习、自适应能力 ,这为更精确描述复杂非线性水文过程提供了可能 .通过对历史数据的学习 ,模型可对水文径流量时间序列进行预报 ,两个实例分析表明模型的可行性和有效性     

过程控制对象数学模型辨识一法及其程序设计

对过程控制对象建模及数据处理问题,目前高专有关教材仍以阶跃响应结合作图法为主,很少介绍以计算机为基础的现代数据处理及实验方法,原因在于算法复杂。这里提出一种基于最小二乘法的建模方法;由对象的传递函数求得差分方程,然后使用最小二乘法做多元线性回归取得参数,并给出了程序结构与仿真结果。     

Nonlinear decoupling controller design based on least squares support vector regression

INTRODUCTION Most practical systems are multivariate nonlin- ear systems. In general, the MIMO (multiple inputs and multiple outputs) systems are coupled. This cou- pling affects the effectiveness of a specific loop con- troller on the corresponding output, and in some case, may become serious and cause many difficulties to the control system design. How to decouple the mul- tivariate systems and design practical controllers is one of the major issues in nonlinear control area. In recen…     

一类非线性系统的广义预测控制

对于时延的非线性系统,将其等价为含有纯滞后的时变线性系统,利用三次样条函数逼近时变参数,利用渐消记忆递推最小二乘法在线辨识多项式的参数以实现时变参数估计,将基于Hammerstein模型的非线性系统线性化.最后运用广义预测控制策略实现对该系统的仿真,结果表明被控对象在广义预测控制算法的控制下系统闭环稳定性好、稳态误差小.     

基于ARMA-NN集成模型的上证指数预测研究

研究表明,大多时间序列可分解为线性部分和非线性部分的组合。融合ARMA模型在捕捉线性关系的优势和神经网络模型强大的非线性映射能力。介绍一种ARMANN集成模型,并对上证指数月收益率进行预测。结果表明集成模型的预测能力显著优于传统单一模型,对指数收益率预测比较准确,有很强的应用价值。     

Robust model predictive control for discrete uncertain nonlinear systems with time-delay via fuzzy model

INTRODUCTION In recent years, research on nonlinear model predictive control has attracted significant attention because most practical processes are nonlinear. In industry process control, model predictive controllers based on linear models (LMPC) are often used to control nonlinear systems. When the operating con- ditions undergo significant changes, the performance of LMPC can deteriorate drastically. Under such conditions, predictive control based on nonlinear models (NMPC) shoul…     

基于神经网络的透气性状态预测

针对烧结过程的时变、强非线性等特点,基于神经网络和粒子群优化算法,提出一种预测透气性状态的集成方法.采用神经网络分别建立透气性预测模型,采用粒子群优化算法对神经网络进行训练,提高预测模型的实时性;进而借助模糊分类器将预测子模型实现有机融合.最后实际运行结果表明,提出的集成模型具有较高的预测精度和较强的自学习能力,并且在工况波动严重的情况下,仍然具有好的预测效果.     

基于AR法的输电塔线体系三维空间风振反应分析

基于某220kV羊角输电塔线体系,采用线性滤波法中的自回归（AR）模型,考虑结构节点间的风速时程相关性,利用MATLAB与VISUAL C＋＋语言的混合编程技术,建立了输电塔线体系的三维空间分析模型,并对输电塔线体系的风振反应进行分析。计算结果表明：该方法具有良好的稳定性和计算效率。对于同风向下的单塔和塔线体系而言,塔线体系的风振响应较弱。通过对比分析单塔、塔线体系及两种规范的风振系数差异,说明采用规范计算风振系数值是偏于保守的。     

具有时滞补偿的网络拥塞控制的研究

经过线性化处理的TCP/AQM拥塞控制模型是一个输入带有时滞的源端链路端组合系统。首先修改了带有延迟的网络拥塞控制模型;计算其平衡状态并进行线性化,采用积分变换算法进行延迟变换为无时滞的线性模型,并建立相应的状态空间模型。在模型矩阵参数抖动但有界限的条件下,应用变结构控制算法设计控制器,基于李雅普诺夫稳定性理论和线性矩阵不等式方法给出了该控制器控制的系统可到达和渐进稳定的可行条件,同时根据该条件设计网络链路端主动队列管理算法。最后,仿真结果表明了该算法的有效性。     

管壳式换热器复合形法优化设计

基于无相变传热过程,建立管壳式换热器优化设计的数学模型．模型以年总费用为目标函数,关联传热面积的非线性方程,适宜采用多变量约束的复合形法．工艺计算结果表明：该模型符合工程实际,复合形法完全可用于该文模型的优化求解．     

基于PSO-SVM模型的网络流量预测研究

针对网络流量高度自相关、随机性和非线性等时间序列特征,采用支持向量机（SVM）模型进行预测。针对SVM模型中参数难以确定的问题,采用粒子群（PSO）算法进行参数寻优,保证预测的精确度。将PSO—SVM模型预测结果与ARIMA自回归移动平均模型、BP神经网络模型预测结果进行比对,PSO—SVM模型具有更高的预测精度,能够更好地反映网络流量的变化规律。     

多变量统计过程控制的现状与展望

统计过程控制是过程监控与故障诊断的方法。在多变量统计过程控制中,传统的方法主要包括主元分析和偏最小二乘,这些方法存在着诸多缺陷。设计时可以应用非线性主元分析、非线性偏最小二乘、动态主元分析、自适应主元分析、多尺度主元分析等方法进行改进。研究中要重视带噪声的监控模型、过程模型信息与经验知识相结合等问题,同时可以把一些新的降维技术用于统计过程控制中。     

CHARACTERISTIC FUNCTIONS OF BILINEAR TIME SERIES MODEL

Bilinear time series models are of importance to nonlinear time seriesanalysis.In this paper,the autocovariance function and the relation between linearand general bilinear time series models are derived.With the help of Volterra seriesexpansion,the impulse response function and frequency characteristic function of thegeneral bilinear time series model are also derived.     

Identification and control of a small-scale helicopter

Designing reliable flight control for an autonomous helicopter requires a high performance dynamics model.In this paper,a nonlinear autoregressive with exogenous inputs （NLARX） model is selected as the mathematical structure for identifying and controlling the flight of a small-scale helicopter.A neural network learning algorithm is combined with the NLARX model to identify the dynamic component of the rotorcraft unmanned aerial vehicle （RUAV）.This identification process is based on the well-known gradient descent learning algorithm.As a case study,the multiple-input multiple-output （MIMO） model predictive control （MPC） is applied to control the pitch motion of the helicopter.Results of the neural network output model are closely match with the real flight data.The MPC also shows good performance under various conditions.     

带约束多项式权重LPV模型辨识算法

针对复杂工业非线性系统建模难度大、精度低等问题,基于多模型插值的变参数线性（ LPV）模型辨识算法,提出双工作点变量条件下的带约束多项式权重函数结构及其参数寻优策略,以有效降低非线性系统辨识的难度并充分保证所建模型的全局稳定性。以高纯度分馏塔这一典型非线性工业过程为研究对象进行LPV模型建模与仿真,获得了较好的输出和阶跃响应曲线拟合结果,验证了LPV模型能够充分反映非线性系统的运行特性以及所提算法的有效性和实用性。     

A predictive controller for joint pitch-roll stabilization

Reduction of roll and pitch motions is critical in improving the safety and operability of a ship. In this paper, a predictive controller for a ship equipped with two pairs of active fins is proposed for joint pitch-roll stabilization. The proposed controller is developed on the basis of ship motion and hydrodynamic force prediction (SMHFP). The SMHFP controller consists of a short-term predictor, a force estimator, and a fin angle allocator. The short-term predictor adopts an autoregressive (AR) approach and serves to forecast ship motions. Then, predicted ship motions are used in an external hydrodynamic force estimator to evaluate the expected stabilizing forces. Finally, the optimal attack angles for active fins are allocated based on external hydrodynamic forces forecasts. The control system of the stabilizing fins and SMHFP controller is integrated into the sea-keeping program. The program was developed based on a weakly nonlinear 2.5D method, which shows better efficiency and accuracy compared with conventional 2D and 3D methods. To evaluate the performance of the proposed controller, numerical simulations of the joint pitch-roll stabilization under various sea states were investigated on a ship model. The results suggest that the SMHFP controller shows satisfactory performance in reducing pitch and roll motions simultaneously.     

Nonlinear model predictive control with guaraneed stability based on pesudolinear neural networks

A nonlinear model predictive control problem based on pseudo-linear neural network (PNN) is discussed, in which the second order on-line optimization method is adopted. The recursive computation of Jacobian matrix is investigated. The stability of the closed loop model predictive control system is analyzed based on Lyapunov theory to obtain the sufficient condition for the asymptotical stability of the neural predictive control system. A simulation was carried out for an exothermic first-order reaction in a continuous stirred tank reactor. It is demonstrated that the proposed control strategy is applicable to some of nonlinear systems.