Boiler-turbine control system design using continuous-time nonlinear model predictive control

A continuous-time nonlinear model predictive controller （NMPC） was designed for a boiler-turbine unit. The controller was designed by optimizing a receding-horizon performance index, with the nonlinear system approximated by its Taylor series expansion with a certain order, the magnitude saturation constraints on the inputs satisfied by increasing the predictive time, and the rate saturation conditions on the actuators satisfied by tuning the time constant of the reference trajectories in a reference governor. Simulation results showed that the controller can drive the drum pressure and output power of the nonlinear boiler-turbine unit to follow their respective reference trajectories throughout a varying operation range and keep the water level deviation within tolerances. Comparison of the NMPC scheme with the generic model control （GMC） scheme indicated that the responses are slower and there are more oscillations in the responses of the water level, fuel flow input and feed water flow input in the GMC scheme when the boiler-turbine unit is operating over a wide range.     

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…     

基于Simulink的汽车行驶控制系统数字仿真

建立汽车行驶控制系统的数学模型,由此获得系统的Simulink模型(仿真模型),对其仿真并用Matlab脚本文件对行驶控制器中比例调节的性能进行分析。     

开关磁阻发电机控制模式研究

提出了开关磁阻发电机低速起动电流斩波控制、高速发电运行角度位置控制的模式,建立了开关磁阻发电机的数值仿真模型,在此基础上重点对角度位置控制方式进行了理论与仿真研究.结果表明,这种控制模式能使系统在宽广速度范围内实现高效发电的目标.     

Strengths-based blended personalized learning: An impact study using virtual comparison group

Abstract

This study describes a strengths-based blended personalized learning model, the implementation of the model over a 4-year period, and the results of an impact study focused on measuring its effectiveness. The model includes many commonly-used features of personalized learning, including (a) competency-based progressions, (b) flexible learning environments, (c) personal learning paths, (d) frequently updated student profiles, and (e) frequent informal and formal measurement. However, it differs from other personalized learning models by including a focus on strengths-based learning. Strengths-based learning identifies and builds upon students’ strengths, supporting their ability to make informed decisions when setting goals and choosing and implementing learning experiences. The longitudinal study took place in a diverse mid-size pre-K to Grade 8 school district in California. The findings suggest that the strengths-based blended personalized learning model is effective in supporting student learning in the academic areas of mathematics, reading, and language usage. Over the 3-year period in which the intervention was gradually implemented, and one year of full implementation, students significantly outpaced their matched student counterparts in all subject areas. The results of the current study further the growing literature in the field of personalized learning by contributing learnings and evidence related to a successful personalized learning model.     

Computer simulation of active suspension based on the full-vehicle model

The current method to solve the problem of active suspension control for a vehicle is often dealt with a quarter-car or half-car model.But it is not enough to use this kind of model for practical applications.In this paper,based on considering the influence of factors such as,seat and passengers a MDOF(multi-degree-of-freedom)model describing the vehicle motion is set up.The MODF model,which is 8DOF of four independent suspensions and four wheel tracks,is more applicable by comparison of its analysis result with some conventional vehicle models.Therefore,it is more suitable to use the 8DOF full-car model than a conventional 4DOF half-car model in the active control design for car vibration.Based on the derived 8DOF odel,a controller is designed by using LQ(linear quadratic)control theory,and the appropriate control scheme is selected by testing various performance indexes.Computer simulation 8is carried out for a passenger car running on a road with step disturbance and random road disturbance expressed by Power Spectral Density(PSD).Vibrations corresponding to ride comfort are derived under the foregoing road disturbances.The response results for uncontrolled and controlled system are compared.The response of vehicle vibration is greatly suppressed and quickly damped.which testifies the effect of the active suspenson.The results achieved for various controllers are compared to invesigate the influence of different control schemes on the control effect.     

Multiobjective optimization and multivariable control of the beer fermentation process with the use of evolutionary algorithms

INTRODUCTIONThefermentationprocesshasgreatscientificandpracticalimportance.Forseveralreasons,qua-litycontrol,forexample,itisimportanttoincludeallkindsoftechnologicaladvancesintheindustrialprocesses.Thisisthemainaimofourresearch,whichisverycomplexduetothenon-linearityofthestudiedphenomena.Themathematicalmodelsfoundinliteratureincludeonlylaboratoyconditions.Amathematicalmodelhasbeendevelopedforthebeerfermentationprocessbecauseoftheadvantagesthatitprovides.Itallowssimulatingwhatcanhappenwhe…     

Machining Complex Oriented Compensation System for Generalized Kinematic Errors

This paper puts forward a machining complex oriented compensation strategy for the generalized kinematic errors(GKEs) According to this strategy,the error map,which is constructed by using the off-line measuring information of the machined workpiece,is not oriented for the machine tool but for the machining complex to compensate the GKEs.The error map is derived by theproposed predictive learning control algorithm(PLCA),which is supported by the information model of machining complex,Experimental results show that the machining complex complex oriented GKEs compensation strategy and the information model based PLCA is effective.     

Multiobjective optimization and multivariable control of the beer fermentation process with the use of evolutionary algorithms

This paper describes empirical research on the model, optimization and supervisory control of beer fermentation. Conditions in the laboratory were made as similar as possible to brewery industry conditions. Since mathematical models that consider realistic industrial conditions were not available, a new mathematical model design involving industrial conditions was first developed. Batch fermentations are multiobjective dynamic processes that must be guided along optimal paths to obtain good results. The paper describes a direct way to apply a Pareto set approach with multiobjective evolutionary algorithms (MOEAs). Successful finding of optimal ways to drive these processes were reported. Once obtained, the mathematical fermentation model was used to optimize the fermentation process by using an intelligent control based on certain rules.     

数字随动系统速度环的控制

通过建立电机模型、速度环的数学模型,分析了不同的控制规律,如常规PID、模糊控制和自适应PI控制等相关控制算法的特点,并选择了一种应用到数字随动系统速度环,实现了较好的控制效果,具有一定的实用价值。     

Fuzzy NN based predictive control and its application to green liquor system

The fuzzy NN predictive control algorithm introduced in this paper uses fuzzy neural network to model the nonlinear MIMO process. Its training method that integrates LS and BP algorithm brings quick convergence. GPC algorithm is used as the predictive component. The fuzzy neural network has six layers, including input layer, output layer and four hidden layers. An application to a MIMO nonlinear process (green liquor system of the recovery system in a pulp factory shows that this algorithm has better performance than normal PID algrithm. Project (No. 20010539) supported by Education Office of Zhejiang Province.     

基于MATCONT的电力系统电压稳定分岔及控制仿真试验

介绍了电力系统ODE模型中引起电压失稳的常见分岔类型及分岔控制的基本概念;运用基于Matlab的数值分岔分析软件MATCONT对一个经典单机—动态负荷系统进行了分岔分析,验证了PQ动态负荷模型系统存在着鞍结分岔(SNB)现象,而RL动态负荷模型系统并无分岔现象产生.为延迟PQ动态负荷模型系统的鞍结分岔点,在原系统中引入了线性状态反馈控制和SVC控制两种分岔控制方法.MATCONT仿真结果显示,这两种控制方法均能够有效延迟鞍结分岔,从而提高系统的电压稳定性,并可通过选择合理的反馈控制器增益及SVC增益获得理想的分岔控制效果.     

Multiplicity Control in Structural Equation Modeling: Incorporating Parameter Dependencies

When structural equation modeling (SEM) analyses are conducted, significance tests for all important model relationships (parameters including factor loadings, covariances, etc.) are typically conducted at a specified nominal Type I error rate (α). Despite the fact that many significance tests are often conducted in SEM, rarely is multiplicity control applied. Cribbie (2000, 2007) demonstrated that without some form of adjustment, the familywise Type I error rate can become severely inflated. Cribbie also confirmed that the popular Bonferroni method was overly conservative due to the correlations among the parameters in the model. The purpose of this study was to compare the Type I error rates and per-parameter power of traditional multiplicity strategies with those of adjusted Bonferroni procedures that incorporate not only the number of tests in a family, but also the degree of correlation between parameters. The adjusted Bonferroni procedures were found to produce per-parameter power rates higher than the original Bonferroni procedure without inflating the familywise error rate.     

基于T—S模型的非线性网络化控制系统H∞鲁棒容错控制

针对一类具有参数不确定性的非线性网络化控制系统,同时考虑网络延时和数据包丢失的影响,利用T—S模型对其进行描述,通过构造Lyapunov—Krasovskii泛函,以线性矩阵不等式形式给出并证明确保非线性网络化控制系tE（NCS）在执行器失效故障时,具有鲁棒容错性依赖的充分条件。仿真算例说明了容错算法的可行性和有效性。     

求解稳态系统优化与控制问题的递推二阶逼近法

本文提出一种递推二阶逼近方法。它利用修正的BFGS公式来构造实际目标函数的Hessian矩阵,通过解一个二阶近似优化问题——这个问题由修正的BFGS公式确定,来得到一个迭代搜索方向。为了获得一个新的迭代点并考虑到实际应用条件的差别,本文给出两种迭代更新策略:一个是牛顿步方法;另一个是一维搜索方法。在一些局部条件下,本文提出的方法具有R—超线性收敛的性质。本文将给出算法的全局收敛性条件和最优性条件,并给出算法收敛速率的估计。最后进行仿真研究,表明新算法的优越性。     

A study of active suspension based on full DOF vehicle model

1Introduction1Because the traditional suspension can hardly meet the demands for either ride comfort or handling stability when the performance of a vehicle’s light weight and high speed are emphasized,more attention has focused on the development of advanced active suspension and its control method has been researched extensively.The current method for solving the problem of active suspension control for a vehicle often deals with a quarter car or a half car model[1-4].But it is not enough t…     

树形层次化组织机构中的分级访问控制模型

在BLP模型基础上提出一个新的分级访问控制模型,模型中建立部门之间的层次关系,提出岗位这一新的概念,简化了安全标记指派这一烦琐工作.通过为岗位指派多个安全标记,实现上下级及平级部门之间的互相沟通,在树形层次中靠得越近的部门,其职员之间可交流的客体密级越高.定义3个层次的访问矩阵,实现多种粒度的灵活的自主访问控制.模型在增加灵活性和实用性的同时保证信息的流动始终处于系统的控制之下,继承了BLP模型最突出的优点,并通过形式化证明的方式对模型进行了验证.     

Single neuron network PI control of high reliability linear induction motor for Maglev

The paper deals with a new model of linear induction motor (LIM) to improve the reliability of the system. Based on the normal equation circuit of LIM considering the dynamic end effect, an equivalent circuit model with compensation of large end effect is constructed when the end effect force at synchronism is of braking character. The equivalent circuit model is used for secondary-flux oriented control of LIM. Single neuron network PI unit for LIM servo-drive is also discussed. The effectiveness of mathematical model for drive control is verified by simulations.     

Integrated statistical and engineering process control based on smooth transition autoregressive model

Traditional studies on integrated statistical process control and engineering process control (SPC-EPC) are based on linear autoregressive integrated moving average (ARIMA) time series models to describe the dynamic noise of the system.However,linear models sometimes are unable to model complex nonlinear autocorrelation.To solve this problem,this paper presents an integrated SPC-EPC method based on smooth transition autoregressive (STAR) time series model,and builds a minimum mean squared error (MMSE) controller as well as an integrated SPC-EPC control system.The performance of this method for checking the trend and sustained shift is analyzed.The simulation results indicate that this integrated SPC-EPC control method based on STAR model is effective in controlling complex nonlinear systems.     

基于比例反馈和变量驱动的 Henon 映象的同步和控制(英文)

在近来混沌同步和控制的各种研究方法的基础上,提出了一种能过比例脉冲控制和变量驱动法达到抑制混沌和连接混沌社经元同步的改进方法．该方法的性能在对高维Ｈｅｎｏｎ映象的混沌控制和同步的研究中得到了验证．在分析研究和仿真实验中,发现了一些非常有意义的结果,这不仅证实了生理学研究成果而且为今后混沌信息记忆和处理提供了新的可能．