源江水厂快滤池提升泵变频控制调节

通过PID控制方式对提升泵进行变频控制,达到确保进水渠水位恒定在(2±0.1)m的范围内的目标。为此,采用工程整定法,经过逐级调试逼近的方式,确定比例增益(P增益):K_p=18、积分增益(I增益):K_i=0、微分增益(D增益):K_d=20的参数组合,同时,也确定了PID控制参数CV的控制上限为60%,控制下限为10%,控制阈值DV为0.03。PID控制循环周期为200ms,同时,介绍了PID控制的数学模型。运行结果表明,通过逐级逼近法确定的控制增益参数组,PID控制效果明显,进水渠水位控制在(2±0.1)m的范围内,达到了恒水位控制目标。     

Neural network based adaptive control via temporal pattern recognition

This paper presents a neural network approach to adaptive control through pattern recognition techniques. Two interconnected backpropagation networks are trained to translate error patterns resulting from sustained set point changes into predictions of mismatch between current internal model parameters, model gain and model time constant, and those which restore desired performance. The network predictions are then used to update a model based PI controller. The strategy is demonstrated on two simulations and a pilot scale process which are undergoing severe changes in model gain and time constant. The strategy compares favorably against a more traditional rule based pattern recognition approach.     

A study of gain scheduling control applied to an exothermic CSTR

This paper describes how gain scheduling control is applied to a continuous stirred tank reactor model. The CSTR process, equipped with a cooling system, is modelled. Based on the resulting nonlinear model, a gain scheduling controller is designed. The gain scheduling follows a scheme denoted bias compensation. Compared to earlier reported gain scheduling schemes, the proposed scheme results in a controller that is less complex, which is advantageous in the controller implementation stage. Numerous simulations are performed, using the gain scheduling controller and two choices of control input to the reactor model. The simulation results indicate that a gain scheduling controller performs better than a linear controller. Simulations using different choices of control input to the reactor model indicate that proper process design is crucial for the controlled process performance.     

An energy‐efficient cost‐effective transient batch rectifier with bottom flashing: Process dynamics and control

Exploring an internal heat source through bottom flashing route, this work introduces a dynamic batch column configuration within the framework of mechanical heat pump system. This batch rectifier with bottom flashing (BRBF) scheme attempts to use the reboiler liquid as a heat exchanging medium in the overhead condenser, thereby avoiding the use of any external coolant stream and reducing the consumption of hot utility in the reboiler. Aiming to operate the proposed transient process unit at an optimal state of energy use, we formulate an online open‐loop control policy that estimates the multiple control actions simultaneously. Furthermore, in order to achieve constant product purity, a gain‐scheduled closed‐loop control system is synthesized with keeping the stability margin constant. Simulating a multicomponent reactive system, the novel BRBF arrangement is evaluated in the aspects of energy savings and cost under both the open‐loop and closed‐loop control modes. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3699–3707, 2015     

计量泵行程调节的鲁棒非脆弱PID控制器设计

This job focuses on the stroke regulation of a class of high-precision metering pumps.A parametertuning method of robust non-fragile PID(proportional-integral-derivative)controllers is proposed with the assumption that a PID controller has additive gain perturbations.An H-infinite robust PID controller can be obtained by solving a linear matrix inequality.This approach can guarantee that the closed-loop control systems is asymptotically stable and the H-infinite norm of the transfer function from the disturbance to the output of a controlled system is less than a given constant to attenuate disturbances.The simulation case shows that the control performance of the proposed strategy is significantly better than the traditional PID approach in the situation with perturbations of controller parameters.     

A time scale-bridging approach for integrating production scheduling and process control

In this paper, we propose a novel framework for integrating scheduling and nonlinear control of continuous processes. We introduce the time scale-bridging model (SBM) as an explicit, low-order representation of the closed-loop input–output dynamics of the process. The SBM then represents the process dynamics in a scheduling framework geared towards calculating the optimal time-varying setpoint vector for the process control system. The proposed framework accounts for process dynamics at the scheduling stage, while maintaining closed-loop stability and disturbance rejection properties via feedback control during the production cycle. Using two case studies, a CSTR and a polymerization reactor, we show that SBM-based scheduling has significant computational advantages compared to existing integrated scheduling and control formulations. Moreover, we show that the economic performance of our framework is comparable to that of existing approaches when a perfect process model is available, with the added benefit of superior robustness to plant-model mismatch.     

COMPENSATOR FOR CONSTANT RELATIVE STABILITY IN PROCESS CONTROL SYSTEMS

Process control systems are designed for a closed-loop peak magnitude of 2 dB, which corresponds to a damping coefficient (ζ) of 0.5 approximately. With this specified constraint, the designer should choose and/or design the loop components to maintain a constant relative stability. However, the manipulative variable in almost all chemical processes will be the flow rate of a process stream. Since the gains and the time constants of the process will be functions of the manipulative variable, a constant relative stability cannot be maintained. Up to now, this problem has been overcome either by selecting proper control valve flow characteristics or by gain scheduling of controller parameters. Nevertheless, if a wrong control valve selection is made then one has to account for huge loss in controllability or eventually it may lead to an unstable control system. To overcome these problems, a compensator device that can bring back the relative stability of the control system was proposed. This compensator is similar to a dynamic nonlinear controller that has both online and offline information on several factors related to the control system. The design and analysis of the proposed compensator is discussed in this article. Finally, the performance of the compensator is validated by applying it to a two-tank blending process. It has been observed that by using a compensator in the process control system, the relative stability could be brought back to a great extent despite the effects of changes in manipulative flow rate.     

无累积罐循环全回流间歇精馏三温控制操作

提出了通过塔顶、塔中上以及塔中3个温度控制进行操作状态转换的无累积罐循环全回流间歇精馏控制方法,并以理想物系--乙醇-正丙醇混合物为分离物系进行了实验研究。通过实验确定了温度控制条件为当塔顶温度稳定后且塔顶和塔中上温差为0.3 ℃时变全回流为全采出操作,当塔中温度升高1.0 ℃时停止全采出转为全回流操作。同时还考察了在不同乙醇投料浓度条件下这种操作的运行情况,发现不同投料浓度对塔顶产品平均纯度的影响并不显著,基本能保持在0.99。最后在相同的投料浓度和操作条件下,对比了这种新型控制方式和双温度控制方式,结果表明三温度控制方式比双温度控制方式操作时间减少了23.3 min,分离效率提高了23.95%,产品浓度提高了1.06%,产品收率提高了1.08%。     

甲醇-苯共沸体系变压精馏分离工艺的动态控制

基于甲醇和苯共沸体系的压敏性,利用Aspen Plus和Aspen Dynamics软件对变压精馏分离该体系的稳态工艺进行了模拟和优化,研究了该工艺的动态特性,提出了控制产品纯度的3种控制结构：基础控制结构、比例控制结构和双比例与温度?组分联合控制结构,通过对控制结构添加±20%的组分和流量干扰测试控制结构的稳定性. 结果表明,基础控制结构基本能实现稳健控制,但不能解决组分干扰引起的产品纯度偏差过大等问题;比例控制结构可实现相对稳健的控制,但改进效果不显著;双比例与温度?组分联合控制结构在受到20%进料和组分干扰后,产品纯度能较快恢复至设定值的99.90%,实现稳健控制.     

QUASILINEARIZATION, PARAMETER ESTIMATION, AND DISTILLATION COLUMN DESIGN

A multicomponent distillation column design problem is solved by the combined use of estimation and quasilinearization. The design problem can be stated as follows: obtain a specified purity of certain products from a given feed mixture by the use of an existing column. The only variable within the designer's control is the reflux ratio. Several different formulations are solved by the quasilinearization approach. It is shown that the concept of treating multi-component distillation as nonlinear boundary value problems forms a powerful and versatile computational tool. Furthermore, this approach can be extended easily to problems with over-specified conditions with the help of some minimization criterion. The technique is also ideally suited for the dynamic control of a distillation column where a constant purity of certain products over time is desired.     

变增益的非线性预测控制算法

采用变增益策略,用输入与稳态输出的映射表示系统的静态非线性,用一个增益为1的ARX模型表示系统的动态模型,代替多数文献中常用的分段线性多模型方法进行非线性系统的预测控制.文中通过对连续搅拌釜反应器(CSTR)的仿真,验证了本算法的有效性.     

AUTOMATED GAIN SCHEDULE GENERATION FOR NONLINEAR ADAPTIVE CONTROL

The generalized minimum variance (GMV) control law includes a penalty function that permits control activity to become more or less vigorous as process character changes. This penalty, if cast as a function of steady state process gain, can enable control of nonlinear processes. To make such an approach easy to implement, a method is detailed for automatically generating and updating a gain schedule while the process is in closed loop. The method is demonstrated on a simulated process that possesses a very nonlinear character. The scope of this paper is limited to single-input single-output, open-loop stable processes     

Development of gain scheduling for trajectory tracking problems in input-output linearizable batch processes

In this paper, a design methodology has been developed for the control of non-autonomous batch processes which typically require good tracking performance. The design, based on the framework of differential geometric methods and linear gain scheduling theory, involves a multi-loop structure. The inner loop is an input-output linearizing state feedback law based on a nominal, time-invariant plant model. The outer loop includes a gain scheduling controller which provides the desired stability and tracking performance in the face of time varying parameters. The procedure is applied to a semi-batch polymethylmethacrylate synthesis problem. The results show excellent tracking performance of the gain scheduling controller.     

An integrated framework for scheduling and control using fast model predictive control

Integration of scheduling and control involves extensive information exchange and simultaneous decision making in industrial practice (Engell and Harjunkoski, Comput Chem Eng. 2012;47:121–133; Baldea and Harjunkoski I, Comput Chem Eng. 2014;71:377–390). Modeling the integration of scheduling and dynamic optimization (DO) at control level using mathematical programming results in a Mixed Integer Dynamic Optimization which is computationally expensive (Flores‐Tlacuahuac and Grossmann, Ind Eng Chem Res. 2006;45(20):6698–6712). In this study, we propose a framework for the integration of scheduling and control to reduce the model complexity and computation time. We identify a piece‐wise affine model from the first principle model and integrate it with the scheduling level leading to a new integration. At the control level, we use fast Model Predictive Control (fast MPC) to track a dynamic reference. Fast MPC also overcomes the increasing dimensionality of multiparametric MPC in our previous study (Zhuge and Ierapetritou, AIChE J. 2014;60(9):3169–3183). Results of CSTR case studies prove that the proposed approach reduces the computing time by at least two orders of magnitude compared to the integrated solution using mp‐MPC. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3304–3319, 2015     

Chiral control of enantiomers through crystallization: Moving from ternary phase diagrams to design spaces

Although chiral purity is a critical quality attribute for many synthetic drugs, current industrial strategies for establishing chiral purity control are underdeveloped. Such strategies have relied on the construction of ternary phase diagrams, system classification, and case‐specific operating policies. These policies have been developed to provide enantiopure solids, regardless of product specification or target. In this article, new operating policies are developed for obtaining solids that meet, but do not exceed, chiral purity specifications for arbitrary systems. These policies can provide significant yield improvements over the current practice. Additionally, this work provides an approach for the creation of design spaces based on the collection of limited, small scale data. This approach has been extended to sequential re‐crystallizations and can be used to determine “global” optimal policies within a synthetic route. © 2018 American Institute of Chemical Engineers AIChE J, 64: 3323–3331, 2018     

Non‐Linear Model Predictive Control: A Personal Retrospective

An overview of non‐linear model predictive control (NMPC) is presented, with an extreme bias towards the author's experiences and published results. Challenges include multiple solutions (from non‐convex optimization problems), and divergence of the model and plant outputs when the constant additive output disturbance (the approach of dynamic matrix control, DMC) is used. Experiences with the use of fundamental models, multiple linear models (MMPC), and neural networks are reviewed. Ongoing work in unmeasured disturbance estimation, prediction and rejection is also discussed.     

Reducing total annualized cost and CO2 emissions in batch distillation: Dynamics and control

In this contribution, the direct vapor recompression approach is introduced in a batch distillation operated at an unsteady state condition. This vapor recompressed batch distillation (VRBD) accompanies an isentropic compressor that runs at a fixed as well as variable speed. Aiming to ensure the optimal use of internal heat source, an open‐loop control policy is proposed for the VRBD that adjusts either the overhead vapor splitting or the external heat supply to the reboiler. Again, the variable speed VRBD additionally involves the manipulation of compression ratio. Developing two alternative configurations of VRBD column, the best heat integrated scheme is attempted to identify in the aspects of energy efficiency and total annualized cost for further advancement. A closed‐loop control algorithm for the best performing variable speed VRBD aiming to meet the end objective of relatively high‐purity product discharged at a constant composition is developed. The separation of a reactive system is considered to illustrate these results and demonstrate the effectiveness of the novel VRBD scheme. Performing simulation tests, it is investigated that the closed‐loop control operation substantially improves not only the distillate purity but also the total amount of product. Achieving significant improvement in thermodynamic efficiency and cost by the controlled heat integrated scheme over its conventional counterpart, finally the attractiveness of the VRBD column by investigating its potential to reduce the greenhouse gas (i.e., CO₂) emissions is shown. © 2013 American Institute of Chemical Engineers AIChE J, 59: 2821–2832, 2013     

Integration of scheduling and control for batch processes using multi‐parametric model predictive control

Integration of scheduling and control results in Mixed Integer Nonlinear Programming (MINLP) which is computationally expensive. The online implementation of integrated scheduling and control requires repetitively solving the resulting MINLP at each time interval. (Zhuge and Ierapetritou, Ind Eng Chem Res. 2012;51:8550–8565) To address the online computation burden, we incorporare multi‐parametric Model Predictive Control (mp‐MPC) in the integration of scheduling and control. The proposed methodology involves the development of an integrated model using continuous‐time event‐point formulation for the scheduling level and the derived constraints from explicit MPC for the control level. Results of case studies of batch processes prove that the proposed approach guarantees efficient computation and thus facilitates the online implementation. © 2014 American Institute of Chemical Engineers AIChE J, 60: 3169–3183, 2014     

网络控制系统中基于PID的死区反馈调度方法

在网络控制系统中,网络负载的加重会使网络资源稀缺,并导致各个子系统控制性能变差．为了改善整个系统的控制品质（QoC）,提出了基于PID死区反馈调度方法,在该方法中,各节点优先级和死区节点是根据每个节点的当前控制品质动态分配和选择的,死区节点上死区范围大小采用PID调节,使得时限错过率稳定在优化的范围之内。仿真结果表明,在网络资源紧缺时,该方法能提高整个系统的控制品质。此外,该算法耗时较少,能满足实际应用中实时性和简便性的要求。     

Gain scheduling PID control for directed self-assembly of colloidal particles in microfluidic devices

Directed self-assembly provides a promising route to fabricate small-scale structures for various engineering applications. The use of the external fields of variable strength and frequency allows for active controls to be implemented. For assembling specific structural features, precise control over a local particle density is often needed, which can be achieved using feedback control. However, the strong nonlinear behavior of directed self-assembly complicates such control. In this work, a gain-scheduling feedback control strategy for directed self-assembly of colloidal particles is presented. The process gain is described by an empirical steady-state model, which is used for scheduling a proportional-integral feedback controller. The automated controller is implemented experimentally in a microfluidic device for directed self-assembly of colloidal particles. The gain-scheduled controller shows a significantly improved dynamic performance compared with a conventional proportional-integral controller over a broad range of operating parameters.