铅锌烧结过程质量产量的智能集成优化控制

针对铅锌烧结过程具有大滞后、多约束的特点,建立烧结块质量产量神经网络预测模型和优化控制模型,提出一种融合聚类搜索粗优化和混沌遗传细优化的智能集成优化控制方法.首先采用模糊聚类算法进行优化样本查询,所得结果作为问题的次优解;然后采用最优保存对简单遗传混沌算法进行二次优化,求取问题的最优解;最后对智能集成方法进行实际验证,系统运行结果表明.该方法较好地实现了高产、优质的生产目标.并且具有全局收敛性和工业有效性,为解决复杂工业过程的优化控制问题提供了一种有效、实用的新思路.     

Steady-state target optimization designs for integrating real-time optimization and model predictive control

In industrial practice, the optimal steady-state operation of continuous-time processes is typically addressed by a control hierarchy involving various layers. Therein, the real-time optimization (RTO) layer computes the optimal operating point based on a nonlinear steady-state model of the plant. The optimal point is implemented by means of the model predictive control (MPC) layer, which typically uses a linear dynamical model of the plant. The MPC layer usually includes two stages: a steady-state target optimization (SSTO) followed by the MPC dynamic regulator. In this work, we consider the integration of RTO with MPC in the presence of plant-model mismatch and constraints, by focusing on the design of the SSTO problem. Three different quadratic program (QP) designs are considered: (i) the standard design that finds steady-state targets that are as close as possible to the RTO setpoints; (ii) a novel optimizing control design that tracks the active constraints and the optimal inputs for the remaining degrees of freedom; and (iii) an improved QP approximation design were the SSTO problem approximates the RTO problem. The main advantage of the strategies (ii) and (iii) is in the improved optimality of the stationary operating points reached by the SSTO-MPC control system. The performance of the different SSTO designs is illustrated in simulation for several case studies.     

Adjoint-based optimization of experimental designs with many control variables

We propose a method for an efficient optimization of experimental designs, using a combination of discrete adjoint computations, Taylor arithmetic and matrix calculus. Compared to the state of the art of using finite differences or the forward mode of automatic differentiation, our proposed approach leads to a reduction of the relative temporal complexity from linear to constant time in the number of control variables and measurement weights. We demonstrate that the advantageous complexity results are not only of theoretical nature, but lead to significant speedups in practice as well. With our implementation we are very close to the theoretical bound of the cheap gradient principle. We present one academic (spatially discretized heat equation) and two industrial application examples (biochemical process/Diesel-oxidation catalysis process) where we achieve speedups that range between 10 and 100. In addition to our core results, we also describe an efficient adjoint approach for the treatment of differential algebraic equations and present adjoint formulas for constrained least-squares problems.     

Development and optimization of the laser-assisted bonding process for a flip chip package

In a fine pitch flip chip package, a laser-assisted bonding (LAB) technology has recently been developed to overcome several reliability and throughput issues in the conventional mass reflow (MR) and thermal compression bonding technology. This study investigated the LAB process for a flip chip package with a copper (Cu) pillar bump using numerical heat transfer and thermo-mechanical analysis. During the LAB process, the temperature of the silicon die was uniform across the entire surface and increased to 280 °C within a few seconds; this was high enough to melt the solder. The heat in the die was quickly conducted to the substrate through the Cu pillar bumps. Meanwhile, the substrate temperature was low and remained constant. Therefore, a stable solder interconnection was quickly achieved with minimal stress and thermal damage to the package. The substrate thickness, the number of Cu bumps, and the bonding stage temperature were found to be important factors affecting the heat transfer behavior of the package. The temperature of the die decreased when a thinner substrate, a higher number of Cu bumps, and a lower bonding stage temperature were used. If the temperature of the die was not sufficiently high, insufficient heat was transferred to the solder to melt it, resulting in incomplete solder joint formation. Thermo-mechanical analysis also showed that the LAB process produced lower warpage and thermo-mechanical strain than the conventional MR process. These results indicated that a LAB process using a selective local heating method would be beneficial in reducing thermo-mechanical stress and increasing throughput for the fine pitch flip chip packages.

     

磨矿分级过程动态优化控制

建立了基于改进粒级质量平衡模型（PBM）的质量指标预测模型和保证过程最优运行的优化计算模型,提出了基于反馈校正的动态优化控制方案.首先由优化模型计算最优控制律,为消除过程扰动及其他不确定因素影响,引入质量指标反馈调节机制;然后智能控制单元根据人工测试和期望质量指标间的偏差对最优控制律进行反馈修正.现场实验结果表明,该方案能够稳定过程产品质量,实现过程节能降耗.     

On-line estimation for process control and optimization applications

Design of Kalman filter type and moving horizon estimators for on-line estimation applications based on first principles models is reviewed. Important design issues are discussed, such as: model development; choice of process noise model and selection of model parameters for on-line estimation; use of asynchronous and delayed measurements; and off-line estimation of fixed but uncertain model parameters. The main conclusion, which is substantiated through application examples, is that robust and reliable estimation applications based on first principles models of considerable complexity, can be designed and implemented for use in an industrial environment.     

基于石墨烯晶体管的多巴胺检测微流控芯片

设计并制备了一种集成液体栅极的石墨烯场效应晶体管的微流控芯片,利用其对多巴胺进行检测,研究了多巴胺分子对石墨烯场效应管转移特性的影响。将石墨烯转移到载玻片上作为导电通道和传感材料集成在微流通道内部,利用剥离(lift-off)工艺制作晶体管的源极和漏极,采用液体栅极的方法对晶体管的转移特性进行测试。同时,结合微电子学的能带理论,从电子迁移的角度出发,讨论了石墨烯和多巴胺之间的氧化还原反应。并采用金属Pt电极作为石墨烯晶体管的栅极,检测到了1 nmol/L浓度的多巴胺溶液。     

Microfluidic blood-plasma separation chip using channel size filtration effect

Microsystem Technologies - Blood separation is an essential first step when performing blood tests for clinical diagnosis purposes. Such tests are increasingly performed using microfluidic systems...     

Trajectory optimization and positioning control for batch process using learning control

Efficiency and accuracy are critical in the motion control of a batch process. This paper proposes a new intelligent motion control method for a batch process based on reinforcement learning (RL) and iterative learning control (ILC). The proposed learning-based motion control method enables the system to learn from its previous experience. The motion control method can be divided into two parts: (1) RL-based trajectory optimization and (2) ILC-based positioning control. Experiments were conducted to demonstrate the effectiveness of the proposed method. The results indicate that the proposed method not only reduces the process time effectively while ensuring system stability, but also achieves excellent positioning accuracy.     

Advanced control and on-line process optimization in multilayer structures

The paper demonstrates the place, role and mutual interaction of advanced control algorithms and on-line set-point optimization in process control structures. First, a multilayer control structure resulting from a functional decomposition is briefly presented. The role and selected realizations of advanced control algorithms, in particular mostly applied now model predictive control (MPC) ones, at direct control and supervisory constraint control layers is discussed. Then possible solutions to on-line set-point optimization, depending of disturbance dynamics, are presented: dynamic set-point optimization including involved structures based on temporal decomposition, and steady-state set-point optimization for cases with disturbance dynamics both much slower than and comparable with the process dynamics. For the last case, important in industrial practice, different structures of interaction and even integration of MPC and steady-state optimization are discussed. The topics are illustrated by briefly presented examples, selected from given references.     

车辆开发过程中驾驶质量的客观评价及优化

针对整车驾驶质量开发中主观评价体系的不足,引入驾驶质量客观评价指标体系。明确驾驶质量开发的客观指标概念和目标曲线,以某款双离合变速器（dual cluth transmission, DCT)车型为研究对象,建立整车驾驶质量仿真模型,对爬坡度、加速度峰值、加速度增益进行分析,并通过优化车辆加速踏板扭矩策略和变速器换挡策略,使客观指标达到整车开发驾驶质量目标。整车驾驶性主观评价试验结果表明整车驾驶性满足开发目标要求,验证客观评价方法的可行性。     

Dynamic multi-objective optimization control for wastewater treatment process

A dynamic multi-objective optimization control (DMOOC) scheme is proposed in this paper for the wastewater treatment process (WWTP), which can dynamically optimize the set-points of dissolved oxygen concentration and nitrate level with multiple performance indexes simultaneously. To overcome the difficulty of establishing multi-objective optimization (MOO) model for the WWTP, a neural network online modeling method is proposed, requiring only the process data of the plant. Then, the constructed MOO model with constraints is solved based on the NSGA-II (non-dominated sorting genetic algorithm-II), and the optimal set-point vector is selected from the Pareto set using the defined utility function. Simulation results, based on the benchmark simulation model 1 (BSM1), demonstrate that the energy consumption can be significantly reduced applying the DMOOC than the default PID control with the fixed set-points. Moreover, a tradeoff between energy consumption and effluent quality index can be considered.

     

基于数据驱动的浓密-压滤过程协调优化控制

针对某选矿厂由于浓密-压滤过程关键变量没有实现在线检测,导致该工序生产操作无序、生产指标难以达标、能耗经济指标高等问题,利用浓密-压滤过程的生产运行数据,提出一种基于数据驱动的浓密-压滤过程协调优化控制方法.首先,通过偏最小二乘(PLS)方法建立浓密-压滤过程的数据模型;然后,在阶梯电价、浓密机运行安全、生产指标的约束...     

Global optimization in design and control of chemical process systems

This paper presents an overview of the recent advances in deterministic global optimization approaches and their applications in the areas of Process Design and Control. The focus is on global optimization methods for (a) twice-differentiable constrained nonlinear optimization problems, (b) mixed-integer nonlinear optimization problems, and (c) locating all solutions of nonlinear systems of equations. Theoretical advances and computational studies on process design, batch design under uncertainty, phase equilibrium, location of azeotropes, stability margin, process synthesis, and parameter estimation problems are discussed.     

基于微球均匀排布的外泌体检测微流控芯片

基于微机电系统(MEMS)微纳加工工艺和聚二甲基硅氧烷(PDMS)软刻蚀技术设计制造了一种外泌体检测芯片,芯片内部包含排列整齐的微柱阵列,用于实现微球在芯片内的均匀排布。利用该芯片成功实现了对外泌体的定量测定,检测下限可达到10~4个/m L,拟合函数的确定系数R~2为0. 996 5。与现有的芯片相比,芯片结构简单,响应快,可重现性好,避免了对外加场的依赖,有着一定的临床应用前景。     

Plant-wide hierarchical optimization and control of an industrial hydrocracking process

Hydrocracking is a crucial refinery process in which heavy hydrocarbons are converted to more valuable, low-molecular weight products. Hydrocracking plants operate with large throughputs and varying feedstocks. In addition the product specifications change due to varying economic and market conditions. In such a dynamic operating environment, the potential gains of real-time optimization (RTO) and control are quite high. At the same time, real-time optimization of hydrocracking plants is a challenging task. A complex network of reactions, which are difficult to characterize, takes place in the hydrocracker. The reactor effluent affects the operation of the fractionator downstream and the properties of the final products. In this paper, a lumped first-principles reactor model and an empirical fractionation model are used to predict the product distribution and properties on-line. Both models have been built and validated using industrial data. A cascaded model predictive control (MPC) structure is developed in order to operate both the reactor and fractionation column at maximum profit. In this cascade structure, reactor and fractionation units are controlled by local decentralized MPC controllers whose set-points are manipulated by a supervisory MPC controller. The coordinating action of the supervisory MPC controller accomplishes the transition between different optimum operating conditions and helps to reject disturbances without violating any constraints. Simulations illustrate the applicability of the proposed method on the industrial process.     

IT process designs for improving information quality and reducing exception handling: A simulation experiment

Exceptions are cases that cannot be handled adequately in automated information processes (IP); but they can significantly affect IP performance. This research develops a model that captures the exception handling activities required in operational-level information processes. The model is sufficiently general to allow evaluation of the performance of information flow processes employing any combination of people and information technologies (IT). It is used to evaluate alternative designs for using IT to improve the quality of the information produced from IP while reducing the resources required for exception handling. In two simulation experiments using the model, advanced IT improved information quality significantly. They did not, however, always reduce flow time and human resource time. These results provide support for justifying the use of advanced IT in organizations for information quality improvement.     

Two dimensional shape optimization using partial control and finite element method for compressible flows

The objective of this study is to determine the two dimensional shape of a body located in a compressible viscous flow, where the applied fluid force is minimized. The formulation to obtain the optimal shape is based on an optimal control theory. An optimal state is defined as a state, in which the performance function defined as the integration of the square sum of the applied fluid forces is minimized due to a reduction in the applied fluid forces. Compressible Navier–Stokes equations are treated as constraint equations. In other words, the body is considered to have a shape that minimizes the fluid forces under the constraint of the Navier–Stokes equations. The gradient of the performance function is computed using the adjoint variables. A weighted gradient method is used as the minimization algorithm. The volume of the body is assumed to be the same as that of the initial body. In the case of the algorithm used in this study, both the creation of a structured mesh around the surface of the body and the smoothing procedure are employed for the computation of gradient. In this study, a remeshing technique based on the structured mesh around the body changing its configuration in the iteration cycle is employed. For the correction to keep the volume constant, the surface coordinates are moved along the radial direction. For the discretization of both the state and adjoint equations, the efficient bubble function interpolation presented previously by the authors [18] is employed. The algorithm, which is known as the partial control algorithm, is applied to the numerical procedure to determine the movement of the coordinates. In the case of the gradient method, in order to avoid the convergence of the final shape to the local minimum shape, the new algorithm, which is called the partial control algorithm, is presented in this study. In numerical studies, the shape determination of a body in a uniform flow field is carried out in 2D domains. The initial shape of the body is assumed to be an elliptical cylinder. The shape is modified by minimizing the applied fluid forces. Finally, the desired shape of a body, whose performance function is reduced and converged to a constant value, is obtained. By carrying out a procedure that involves the use of the partial control algorithm, the desired shape of a body, whose performance function is reduced further, is obtained. Stable shape determination of a body in a compressible viscous flow is carried out by using the presented method. It is indicated that the optimal shape can be obtained by using the partial control algorithm.