SMB色谱分离过程的动态矩阵控制

针对SMB色谱分离过程的工作原理,分析了现有系统开环不加控制时过程运行的缺陷,在机理模型的基础上通过辨识得到了对象局部简化模型。根据此模型设计了多变量动态矩阵控制器,实现了过程的预测控制。通过仿真实验分别比较了系统在不加控制和DMC控制时在轨迹跟踪和扰动抑制方面的性能,结果表明采用DMc控制算法的SMB过程,比不加控制时的系统有良好的性能和优越性,从而为系统的实际运行提供理论基础。     

Modeling and simulation of a SMB chromatographic process designed for enantioseparation

This paper focuses on modeling of a simulated moving bed process (SMB) dedicated to the separation of racemic mixtures. In the first approach, a true moving bed model is derived, which assumes an equivalent counter-current movement of the solid phase. The good agreement between the model and the real system is demonstrated with experimental results. Then, a more rigorous approach is developed, which considers the system as an arrangement of static chromatographic columns and takes into account periodic switching. Attention is focused on model formulation and numerical solution techniques in order to develop efficient dynamic simulation programs.     

基于Profibus-DP现场总线的多功能色谱分离装置控制系统设计

为了实现多功能色谱分离装置的精准化控制,加速模拟移动床色谱纯化分离速度,设计基于Profibus-DP现场总线的多功能色谱分离装置控制系统;以STM32F103微处理器作为底层控制设备,连接Profibus-DP协议芯片、VPC3与RS-485接口电路,转化从站地址电路与设定应用模块,利用模拟移动床控制回路,完成Profibus-DP现场总线的硬件电路设计;建立梯度SMB色谱,采用异步切换方式,控制变浓度进料的实际操作行为,分离处理模拟移动床多功能色谱,结合多功能色谱分离装置的控制原理,运用气相色谱法,分析色谱分离过程中的基质效应形式,实现多功能色谱分离装置控制系统软件设计;实验结果表明,基于Profibus-DP现场总线控制系统的模拟移动床色谱纯化分离速度较快,能够有效满足多功能色谱分离装置精准化控制的操作需求.     

Efficient moving horizon state and parameter estimation for SMB processes

In this paper, a moving horizon state and parameter estimation scheme for chromatographic simulated moving bed SMB processes is proposed. The simultaneous state and parameter estimation is based on a high-order nonlinear SMB model which incorporates rigorous models of the chromatographic columns and the discrete shiftings of the inlet and outlet ports. The estimation is performed using sparse measurement information: the concentrations of the components are only measured at the two outlet ports (which are periodically switched from one column to the next) and at one fixed location between two columns. The goal is to reconstruct the full state of the system, i.e. the concentration profiles along all columns, and to identify critical model parameters reliably such that the estimated model can be used in the context of online optimizing control. The state estimation scheme is based upon a deterministic model within the prediction horizon, state noise is only present in the state and the parameters prior to and at the beginning of the horizon. By solving the optimization problem with a multiple-shooting method and applying a real-time iteration scheme, the computation times are such that the scheme can be applied online. Numerical simulations of a validated model for a separation problem with nonlinear isotherms of the Langmuir type demonstrate the efficiency of the algorithm.     

Genetic programming through bi-objective genetic algorithms with a study of a simulated moving bed process involving multiple objectives

A new bi-objective genetic programming (BioGP) technique has been developed for meta-modeling and applied in a chromatographic separation process using a simulated moving bed (SMB) process. The BioGP technique initially minimizes training error through a single objective optimization procedure and then a trade-off between complexity and accuracy is worked out through a genetic algorithm based bi-objective optimization strategy. A benefit of the BioGP approach is that an expert user or a decision maker (DM) can flexibly select the mathematical operations involved to construct a meta-model of desired complexity or accuracy. It is also designed to combat bloat – a perennial problem in genetic programming along with over fitting and under fitting problems. In this study the meta-models constructed for SMB reactors were compared with those obtained from an evolutionary neural network (EvoNN) developed earlier and also with a polynomial regression model. Both BioGP and EvoNN were compared for subsequent constrained bi-objective optimization studies for the SMB reactor involving four objectives. The results were also compared with the previous work in the literature. The BioGP technique produced acceptable results and is now ready for data-driven modeling and optimization studies at large.     

Decentralised control of chromatographic simulated moving bed processes based on wave front reconstruction

The behaviour of chromatographic simulated moving bed processes is described by the movement of concentration profiles through a circle of separation columns. A closed-loop control manipulates the profiles in order to meet demands concerning specified product purity and disturbance attenuation. If steep wave fronts of the concentration profiles occur, the controlled variables undergo fast changes in case of a transient of the process. In this case, a reconstruction of the wave fronts is necessary for a successful control.A simple and effective decentralised controller structure is proposed based on cascaded discrete-time PI controllers. On-line product purity measurements and the reconstructed wave fronts are used for control purposes. Two kinds of process models are used: a rigorous model for dynamic simulations, and strongly simplified plant models for the design of the wave front reconstruction and the controller. The latter models are identified based on experimental step tests with the reference plant and numerical simulations. The performance of the control system is evaluated by numerical simulations.     

Cycle to cycle adaptive control of simulated moving bed chromatographic separation processes

The simulated moving bed (SMB) technology is increasingly applied in various fields, ranging from the food to the pharmaceutical sectors, for the chromatographic separation of fine (bio)chemicals. In this study, an adaptive controller acting on the fluid flow rates and commutation period is used to regulate the spatial location of the adsorption and desorption waves, and in turn the purity and productivity of the raffinate and extract effluents. This controller is based on a simple discrete-time model of the concentration fronts movement, derived from wave theory. A simple parameter adaptation scheme makes this controller robust to parameter uncertainties and drifts, and allows process start-up with minimum a priori knowledge of the separation parameters. In this study, the performance of the controller is demonstrated for two different applications: the separation of fructo-oligosaccharides (linear isotherms) and cyclopentanone–cycloheptanone (competitive Langmuir isotherms). Different plant/sensor configurations are also examined, indicating the potential of the control strategy even with reduced measurement information.     

Automatic control of the simulated moving bed process for C8 aromatics separation using asymptotically exact input/output-linearization

An approach to automatic control of the simulated moving bed process (SMB) applied to the separation of C₈ aromatics is presented. The principle of asymptotically exact input/output-linearization is used. The controller is based on a nonlinear state estimator using the true moving bed model (TMB). The estimator receives measurement data from four spectroscopic measurement cells. The problem of moving measurement positions with respect to the TMB model is addressed. An exactly linearizing feedback of the estimated states is designed using the nonlinear TMB model equations. The performance of the controller is shown in simulations using a detailed SMB model as a representative of the real process.     

登月软着陆轨道优化算法研究

月球软着陆轨道优化是月球探测中的关键技术之一,研究了基于燃料最优的定常推力月球探测器软着陆轨道优化问题.在优化算法中,首先对软着陆轨道动力学方程做归一化处理,经过将软着陆轨道离散化,应用函数逼近法拟合推力控制角,从而将轨道优化问题转化为参数优化问题,最后设计了蛙跳算法作为搜索优化方法.仿真结果表明设计的轨道较好地满足了所要求的约束条件,同时蛙跳算法具有很高的优化精度,并且应用比较简便,可以应用于登月软着陆的轨道优化设计任务.     

自动化控制下机械手臂运动轨迹研究

对机械手臂运动轨迹进行优化控制,能改善机械手臂的自动控制性能。为了提高机械臂的控制稳健性,提出一种基于变结构模糊PID控制的机械手臂运动轨迹优化控制模型。首先采用末端效应逆运动学模型构建机械手臂的运动规划约束参量数学模型,采用七自由度运动空间重构方法建立机械手臂运动的动力学方程。然后通过纵向定常运动,分析建立机械手臂整定控制目标函数,求解机械臂在抓取作业过程中的最佳导引控制律,采用变结构模糊PID控制方法进行运动轨迹的误差修正,实现机械臂自动控制优化。最后通过仿真实验进行控制性能测试,结果表明,采用该方法进行机械手臂运动轨迹控制的精度较高,对机械臂位形变化轨迹的预测准确性较好。     

SMB色谱分离过程的Matlab仿真

基于考虑因素全面的综合速率模型,通过对柱向和吸附颗粒径向模型采用有限元法和正交配点法进行离散化,利用Matlab ODE求解器对离散化得到的常微分方程进行数值求解,在此基础上设计了仿真软件。以具体仿真实例,验证了所用方法的可行和有效性。最后分析了切换时间和流量变化对分离性能的影响。     

反临拦截弹中制导弹道在线优化设计

为了实现反临拦截弹中制导段的弹道在线优化,基于邻域最优控制(NOC)理论和改进间接高斯伪谱法(GPM)设计一种弹道在线生成算法.根据临近空间拦截作战特点设计弹道优化模型,基于NOC理论推导关于修正状态量和协态量的两点边值问题.对横截条件进行二阶变分,通过逆向递推将终端最优协态修正值表示成跟踪偏差和终端约束修正量的表达式.将拦截弹的当前状态量作为初始约束值,终端最优协态修正值作为干扰量,利用标称弹道数据,基于改进间接GPM求得控制修正量.仿真结果表明,所提出的方法可以快速生成一条修正弹道,且具有较高的终端修正精度.     

Neural network-based identification of SMB chromatographic processes

In this contribution, the identification problem for the control of nonlinear simulated moving bed (SMB) chromatographic processes is addressed. For process control the flow rates of extract, desorbent, and recycle of the SMB process, and the switching time are the manipulated variables. But these variables influence the process in a strongly coupled manner. Therefore, a new set of input variables is introduced by a nonlinear transformation of the physical inputs, such that the couplings are reduced considerably. The front positions of the axial concentration profile are taken as model outputs. Multilayer feedforward neural networks (NN) are utilized as approximating models of the nonlinear input–output behavior. The gradient distribution of the model outputs with respect to the inputs is used to determine their structural parameters and the network size is chosen by the SVD method. To illustrate the effectiveness of the identification method, a laboratory scale SMB process is used as an example. The simulation results of the identified model confirm a very good approximation of the first principles models and exhibit a satisfactory long-range prediction performance.     

基于Matlab的SMB色谱分离过程计算机仿真研究

针对考虑因素全面的SMB综合速率模型，采用有限元方法和正交配点法分别对柱向和吸附剂颗粒径向模型进行离散化，利用Matlab ODE求解器对SMB过程进行了数值求解，并编制了SMB过程仿真软件。在此基础上进行了一个SMB分离实例仿真，分析了切换时间和流量变化对分离性能的影响，验证了SMB过程分离性能的参数敏感性，提出了对系统实施先进控制的必要性。     

网联车辆有限时间分布式轨迹优化和协同控制

提出一种基于分层控制框架的网联车辆有限时间轨迹优化和协同控制方法.首先,在上层,为了最小化车辆间的间距误差,采用有限时间分布式优化算法构造车辆参考模型,产生最优轨迹信号;在下层,设计基于终端滑模的跟踪控制器使得车辆在有限时间内跟踪最优轨迹信号,并克服扰动等不确定因素的影响.然后,通过李雅普诺夫分析,严格验证控制系统的稳定性.最后,通过数值仿真结果表明了所提出方法的有效性.     

基于群智能-一致性理论的无人机编队全过程飞行航迹规划方法

针对无人机编队执行任务全过程飞行规划问题,提出一种基于多步粒子群优化的无人机编队航迹规划算法.首先,对无人机和执行任务策略进行建模,将编队执行任务全过程划分为编队成形、执行任务、返航、解散和无人机降落5个阶段,设计不同阶段的飞行策略;其次,针对不同的终端约束条件,设计多类多层优化指标,提出多步粒子群算法,并引入模型预测控制滚动优化航路点,得到适用于不同阶段的能严格满足约束条件的航路规划方法;然后,建立旋转坐标系,将航路点信息转换为编队控制律中的理想航向和高度信息,得到能通过航路点的编队控制算法;最后,利用编队控制算法去执行航路规划方法给出的航路点,生成航迹,得到编队航迹规划算法.仿真结果表明,所提规划方法比传统方法更适用于编队飞行,能为编队规划执行任务全过程的平滑航迹,具有良好的通用性.     

Decentralized control and identified-model predictive control of divided wall columns

As a thermal separation method, distillation is one of the most important separation technologies in the chemical industry. Given its importance, it is no surprise that increasing efforts have been made in reducing its energy inefficiencies. A great deal of research is focused in the design and optimization of the divided-wall column (DWC). Its applications are still reduced due to distrust of its controllability and robustness. Previous references have studied the decentralized control of DWC but still few papers deal about model predictive control (MPC) applied to DWC.In this work we present a decentralized control of both a divided-wall column along with its equivalent MPC schema, both approaches are compared. Instead of building a rigorous model or performing the step test to an existing plant, the MPC model is obtained by identification of a rigorous simulation. An ARX model is demonstrated to represent adequately the DWC column behavior. This approach might be very convenient if plant testing is not available.     

发酵过程混合建模与优化控制新方法

针对当前微生物发酵过程存在因为生物传感器不具备足够的准确性和灵敏性,实验时的菌液和产物浓度等生化指标难以实时监测和控制等缺点,提出了采用量子粒子群优化算法(QPSO)优化最小二乘支持向量机(LSSVM)参数的QPSO-LSSVM混合建模新方法,并用于多粘菌素的发酵过程建模;同时,基于此模型,采用QPSO算法对pH值与溶解氧浓度Do控制轨线进行优化研究;首先,利用LSSVM进行发酵过程的建模,然后采用QPSO对LSSVM建模过程中的重要参数进行优化调整,形成QPSO-LSSVM混合建模与优化控制方法;仿真结果表明,该方法得到的模型能取得更好的预测效果,优化后的pH值与Do浓度控制轨线能够提高最终的产物浓度;该方法用于发酵过程的建模和重要参数的优化控制是可行的、有效的。     

一类无冲突轨迹规划方案

在新一代空中交通管理自动化系统实施方案中,航迹规划模块在基于航迹的航空器运行过程中扮演着重要角色.为了在大流量、高密度和小间隔条件下获取多航空器无冲突轨迹,针对不同的航路空间分布结构,基于航路冲突点保护区竞争机制,构建了空域多航空器极大代数耦合模型和多航空器冲突预调配模型,根据管制间隔约束建立了模型输入、状态和输出之间的约束关系.采用调整航空器过冲突点时刻和初始放行时刻两种策略,提出了一种多航空器轨迹规划优化模型.算例分析表明,所提出的多航空器轨迹规划模型可行有效.