Nonlinear dynamic behaviors and control based on simulation of high-purity heat integrated air separation column

In this paper, the dynamic behaviors on the basis of simulation for high-purity heat integrated air separation column (HIASC) are studied. A nonlinear generic model control (GMC) scheme is proposed based on the nonlinear behavior analyses of a HIASC process, and an adaptive generic model control (AGMC) scheme is further presented to correct the model parameters online. Related internal model control (IMC) scheme and multi-loop PID (M-PID) scheme are also developed as the comparative base. The comparative researches are carried out among these linear and nonlinear control schemes in detail. The simulation research results show that the proposed AGMC schemes present advantages in both servo control and regulatory control for the high-purity HIASC.     

Batch distillation employing cyclic rectification and stripping operations

Several strategies have been proposed to increase the operating efficiency of batch distillation. In this study, conventional batch rectification and inverted batch stripping are used cyclically to promote high product flow rates for a binary fractionation. Process controls are implemented to maintain constant product purity specifications by varying the slope of the operating line. While rectifying, the light component is removed as distillate, concentrating the heavy component in the reboiler. As a result, the distillate rate decreases with time. The column is then changed from rectification to stripping modes, and the heavy component is removed as bottoms product, concentrating the light component in the distillate drum. This causes the bottoms rate to diminish with time, and the column is once again converted back to rectifying mode. Cyclic operation, transitioning from batch rectifying to stripping back to rectifying, continues until all of the initial charge is fractionated or is combined with a new charge. The fractionation of ethanol and 1-propanol using the proposed operating strategy is shown to provide several advantages including energy and time savings when compared to conventional batch or inverted batch distillation alone.     

Neuro-estimator based GMC control of a batch reactive distillation

In this paper, an artificial neural network (ANN)-based nonlinear control algorithm is proposed for a simulated batch reactive distillation (RD) column. In the homogeneously catalyzed reactive process, an esterification reaction takes place for the production of ethyl acetate. The fundamental model has been derived incorporating the reaction term in the model structure of the nonreactive distillation process. The process operation is simulated at the startup phase under total reflux conditions. The open-loop process dynamics is also addressed running the batch process at the production phase under partial reflux conditions. In this study, a neuro-estimator based generic model controller (GMC), which consists of an ANN-based state predictor and the GMC law, has been synthesized. Finally, this proposed control law has been tested on the representative batch reactive distillation comparing with a gain-scheduled proportional integral (GSPI) controller and with its ideal performance (ideal GMC).     

Nonlinear model-based control algorithm for a distillation column using software sensor

This paper presents the design of model-based globally linearizing control (GLC) structure for a distillation process within the differential geometric framework. The model of a nonideal binary distillation column, whose characteristics were highly nonlinear and strongly interactive, is used as a real process. The classical GLC law is comprised of a transformer (input-output linearizing state feedback), a nonlinear state observer, and an external PI controller. The tray temperature based short-cut observer (TTBSCO) has been used as a state estimator within the control structure, in which all tray temperatures were considered to be measured. Accordingly, the liquid phase composition of each tray was calculated online using the derived temperature-composition correlation. In the simulation experiment, the proposed GLC coupled with TTBSCO (GLC-TTBSCO) outperformed a conventional PI controller based on servo performances with and without measurement noise as well as on regulatory behaviors. In the subsequent part, the GLC law has been synthesized in conjunction with tray temperature based reduced-order observer (GLC-TTBROO) where the distillate and bottom compositions of the distillation process have been inferred from top and bottom product temperatures respectively, which were measured online. Finally, the comparative performance of the GLC-TTBSCO and the GLC-TTBROO has been addressed under parametric uncertainty and the GLC-TTBSCO algorithm provided slightly better performance than the GLC-TTBROO. The resulting control laws are rather general and can be easily adopted for other binary distillation columns.     

A comparison of a novel robust decentralised control strategy and MPC for industrial high purity,high recovery,multicomponent distillation

In this work we have developed a novel, robust practical control structure to regulate an industrial methanol distillation column. This proposed control scheme is based on a override control framework and can manage a non-key trace ethanol product impurity specification while maintaining high product recovery. For comparison purposes, a MPC with a discrete process model (based on step tests) was also developed and tested. The results from process disturbance testing shows that, both the MPC and the proposed controller were capable of maintaining both the trace level ethanol specification in the distillate (X_D) and high product recovery (β). Closer analysis revealed that the MPC controller has a tighter X_D control, while the proposed controller was tighter in β control. The tight X_D control allowed the MPC to operate at a higher X_D set point (closer to the 10 ppm AA grade methanol standard), allowing for savings in energy usage. Despite the energy savings of the MPC, the proposed control scheme has lower installation and running costs. An economic analysis revealed a multitude of other external economic and plant design factors, that should be considered when making a decision between the two controllers. In general, we found relatively high energy costs favour MPC.     

Nonlinear predictive control of a drying process using genetic algorithms

A nonlinear predictive control technique is developed to determine the optimal drying profile for a drying process. A complete nonlinear model of the baker's yeast drying process is used for predicting the future control actions. To minimize the difference between the model predictions and the desired trajectory throughout finite horizon, an objective function is described. The optimization problem is solved using a genetic algorithm due to the successful overconventional optimization techniques in the applications of the complex optimization problems. The control scheme comprises a drying process, a nonlinear prediction model, an optimizer, and a genetic search block. The nonlinear predictive control method proposed in this paper is applied to the baker's yeast drying process. The results show significant enhancement of the manufacturing quality, considerable decrease of the energy consumption and drying time, obtained by the proposed nonlinear predictive control.     

用户多电源供电储能系统蓄电池充放电控制研究

为了提升蓄电池充放电控制的准确性,对用户多电源供电储能系统蓄电池充放电控制进行研究。通过设计双向AC/DC变换器实现蓄电池充放电控制,以双向AC/DC变换器一般数学模型为基础,加入同步旋转坐标系构建双向AC/DC变换器dq模型,提升蓄电池充放电控制的准确性;并网运行时,双向AC/DC变换器利用PQ控制策略,完成蓄电池充放电过程中功率平衡控制;离网运行时,双向AC/DC变换器利用V/f控制策略,完成蓄电池充放电过程中电压与频率的平衡控制。实验结果表明,所研究蓄电池充放电控制策略能够有效控制蓄电池充放电,提升蓄电池充放电过程中功率平衡控制的准确性。     

基于平均功率平衡控制的磁悬浮分子泵电力失效补偿方法

高速磁悬浮涡轮分子泵（Turbo Molecular Pump, TMP）因其高能量密度、微振动、无需润滑等优点被广泛应用于工业领域,但外部电源失效时,高速转子跌落后与保护轴承产生剧烈撞击和摩擦,将给系统带来致命损害。针对以上问题,提出一种基于平均功率平衡法的电力失效补偿控制（Power Failure Compensation Control, PFCC）方法。首先,设计电机能量回馈电路;其次,对Buck-Boost变换器进行数学建模,设计一种双环非线性控制器,其中电流内环使用滑模控制,电压外环使用平均功率平衡控制（Average Power Balance Control, APBC）,并利用Lyapunov函数推导出系统的稳定性条件;最后,通过搭建磁悬浮分子泵PFCC实验平台,对所提出的方法进行实验验证。结果表明：本文所提出的方法具有快速响应和输出鲁棒性,磁悬浮转子由额定转速21000 r/min降至3900 r/min时跌落,电机能量转化效率为96.6%,提高了磁轴承系统的安全性。     

适用于镁海水电池的能量变换系统设计

本文设计了一种适用于镁海水电池供电的能量变换系统,针对镁海水电池输出特性软、电压低的问题,对传统非隔离型三端口变换器进行优化,使电压增益得到进一步提高。基于此变换器拓扑,考虑镁海水电池输出特性和变换器载荷特性,提出一种适用于载荷突变的DC/DC变换系统能量管理策略,通过控制能量在系统内任意两个端口间的流动,实现源、荷间功率动态平衡;同时,根据镁海水电池的输出特性,在系统能量管理中引入一种基于改进灰狼算法的最大功率点追踪方法,进一步提高了镁海水电池的能量转换效率。最后通过仿真和实验证明,载荷功率在0.36和1.2 W跳变时,变换器能相应完成模式间的切换,在保证输出电压稳定在12 V的前提下,实现了对输出电流30和100 mA的灵活控制,验证了该能量变换系统软硬件设计合理性。     

电场诱导W-C-Co体系燃烧合成数学模型及机理研究

基于电场辅助分析法是对体系施加外加电场,通过对电场的控制来控制合成过程的一种方法。本文在前期实验结果的基础上,基于能量守恒定律,建立数学模型,得出W-C-Co体系燃烧合成时转化率随反应时间转变关系曲线,发现电场作用下W-C-Co体系燃烧合成符合金斯特林格扩散模型,得出了W-C-Co体系燃烧合成反应机理。     

Feedback linearization based control of a variable air volume air conditioning system for cooling applications

Design of a nonlinear control system for a Variable Air Volume Air Conditioning (VAVAC) plant through feedback linearization is presented in this article. VAVAC systems attempt to reduce building energy consumption while maintaining the primary role of air conditioning. The temperature of the space is maintained at a constant level by establishing a balance between the cooling load generated in the space and the air supply delivered to meet the load. The dynamic model of a VAVAC plant is derived and formulated as a MIMO bilinear system. Feedback linearization is applied for decoupling and linearization of the nonlinear model. Simulation results for a laboratory scale plant are presented to demonstrate the potential of keeping comfort and maintaining energy optimal performance by this methodology. Results obtained with a conventional PI controller and a feedback linearizing controller are compared and the superiority of the proposed approach is clearly established.     

SA904L钢板焊接工艺探讨

某公司为年产40000t差别化腈纶技术改造项目承制一台醋酸去除塔再沸器。该设备的使用介质腐蚀性较强,为此,设计上选用了904L不锈钢,本文经可焊性分析后,从焊接材料、焊接工艺参数的选择入手,进行了焊接工艺性试验,找出了合适的焊接规范,并在实际产品的焊接中进行了严格的质量控制,使该产品的制造顺利完成。     

采用双螺杆压缩机的机械蒸汽再压缩污水处理系统试验研究

对国内自主研发的采用双螺杆压缩机的60 t/d双效机械蒸汽压缩(Mechanical vapor compression,MVC)采油污水处理系统进行调试及变工况试验研究,分析压缩机转速、一效进水温度和二效出水循环量对系统产水量及产水能耗的影响,为系统优化设计及市场化提供参考。研究表明,系统能稳定运行,在60 t/d原料水处理量下,系统产水量约为1.03 t/h,每吨水处理能耗为35 k W·h;双螺杆压缩机工作过程喷入的冷却水水质需要满足一定要求,避免转子及机壳表面结垢发生故障;随压缩机转速升高,系统产水量升高,产水能耗存在最低值,即压缩机转速及系统运行工况存在最优匹配关系;系统产水量及产水能耗随一效进水温度升高而分别升高和降低,且这种规律不受压缩机转速影响;随着二效出水循环量的升高,系统产水量逐渐升高,升高幅值随一效入口温度升高而降低。     

基于模糊-PID控制和变频调速的高速液压拉伸机控制系统研究

针对拉伸机的速度控制，提出了拉伸机模糊－PID控制和变频调速的控制方式，实践表明，它能有效的实现拉伸速度的控制要求，达到节能降耗，提高制品质量和降低开裂率的目的。     

抽油机变频节能系统的研制

研发了一套抽油机专用变频节能装置,在一定程度上降低了抽油机的泵效。整套装置通过独特设计的继电接触控制线路,可实现变频/工频运行的自动切换。在系统设计中,DSC和STC单片机各司其能,通过串行通讯协调工作,整个系统能够实现电机变频软启停。     

Computer-assisted choice of electrohydraulic servosystems for manipulation robots using complete mathematical models

In this paper, a computer procedure for the choice of electrohydraulic servosystems of manipulation robots is described. Mathematical models based on this procedure represent complete dynamic models of manipulation robots where all dynamic effects are included. Two types of mathematical model of electrohydraulic servosystems are considered: a linearized mathematical model with fixed parameters (time-invariant model) and a linearized mathematical model with variable parameters (time-varying model). Based on exact dynamic analysis, interactive procedures for optimal choice of electrohydraulic actuators, using both types of mathematical models are derived. A criterion is based on the minimum energy consumption for trajectory realization. Selection procedures are given on a typical example of manipulation robot. Also, programmed control calculated using both types of linearized models is compared with programmed control using exact nonlinear models of servosystems. It is shown that the linearized model with variable parameters represents qualitative dynamic behaviour of manipulation robots.     

基于切换方法的倒立摆起振和平衡控制

采用切换控制的方法实现环型倒立摆的起振和平衡控制。通过设计非线性前馈控制器实现倒立摆的起振控制,当环型倒立摆达到非稳定平衡点附近的时候,切换到线性状态反馈控制器实现倒立摆的镇定控制。改变线性状态反馈控制器的输入还可以实现环型倒立摆的旋转平衡控制。仿真验证了控制策略的有效性。     

基于随机模型预测控制的四驱混合动力汽车能量管理

基于随机模型预测控制基本原理,研究了四驱混合动力汽车的能量优化管理。采用马尔可夫模型预测加速度变化过程,通过计算得到混合动力汽车未来需求转矩。在保证电池荷电状态平衡的前提下,以燃油经济性最优为目标,建立混合动力汽车能量管理优化模型。针对建立的非线性优化模型,采用动态规划算法进行有限时域内的滚动求解。将提出的控制策略在dSPACE中进行软件在环仿真试验。研究结果表明,随机模型预测控制策略可以实现四驱混合动力汽车基本的能量管理,可在保证各动力部件良好工作状况的前提下,提升燃油经济性。与基于恒值模型的预测控制策略相比,随机模型预测控制策略下的平均燃油经济性提升了8.30%,优化结果接近有先验知识的预测控制策略。     

对2024铝合金疲劳裂纹扩展寿命进行预测

通过二维弹塑性有限元计算得到Ⅰ型静态裂纹在常幅疲劳载荷下裂纹尖端塑性应变能,进而获得裂纹尖端塑性应变能和应力强度因子幅值的非线性关系;根据能量平衡概念,建立了裂纹扩展速率与裂纹尖端塑性应变能的关系。由此得到一种基于裂纹尖端塑性应变能的疲劳裂纹扩展寿命预测模型,利用该模型预测了中心裂纹平板的疲劳裂纹扩展寿命,预测结果与试验值吻合得很好。     

磨矿效果回归模型的试验性研究

依据转速率、填充率、产品产量和磨矿效率多个因变量与自变量在实际磨矿过程中的相关关系，以1台中600mm×400mm球磨机样机的组合试验数据为基础，根据最小二乘法原理建立转速率、填充率与产品产量和磨矿粒度的回归模型。通过模型的建立，计算出细粒度和粗粒度产品产量的极值，并且在磨矿效率回归模型的基础上，得到比能耗最低时转速率和填充率的值；同时，将试验数据进行图形转化，进而直观形象地反映出产品产量变化的趋势。