Further developments in the new approach to boundary condition iteration in optimal control

In solving the boundary value problem resulting from the use of Pontryagin's maximum principle, a transformation matrix is used to relate the sensitivity of the final state to the initial state. This avoids the need to solve the (n × n) differential equation to give the transition matrix, and yields very rapid convergence to the optimum. To ensure convergence, iterative dynamic programming (IDP) is used for a number of passes to yield good starting conditions for this boundary condition iteration procedure. Clipping technique is used to handle constraints on control. Five optimal control problems are used to illustrate and to test the procedure.     

Stochastic maximum principle for optimal control under uncertainty

Optimal control problems involve the difficult task of determining time-varying profiles through dynamic optimization. Such problems become even more complex in practical situations where handling time dependent uncertainties becomes an important issue. Approaches to stochastic optimal control problems have been reported in the finance literature and are based on real option theory, combining Ito’s Lemma and the dynamic programming formulation. This paper describes a new approach to stochastic optimal control problems in which the stochastic dynamic programming formulation is converted into a stochastic maximum principle formulation. An application of such method has been reported by Rico-Ramirez et al. (Computers and Chemical Engineering, 2003, 27, 1867) but no details of the derivation were provided. The main significance of this approach is that the solution to the partial differential equations involved in the dynamic programming formulation is avoided. The classical isoperimetric problem illustrates this approach.     

基于PSO-控制变量参数化混合策略的间歇化工过程优化控制

控制变量参数化方法作为一种化工过程动态优化的梯度搜索算法，其求解效率过于依赖初始给定轨迹。目前初始轨迹一般都是设定在边界值或中间值，缺乏科学依据，从而大大影响了算法的收敛速度。针对这一问题，提出了一种粒子群优化(PSO)与控制变量参数化方法混合的策略，首先利用粒子群优化对间歇化工过程最优控制量进行求解，结果作为控制变量参数化方法初始给定轨迹，进行二次优化。双层优化的混合策略提高了控制变量参数化方法的收敛速度和粒子群优化算法的求解精度。将混合策略应用于两个间歇化工过程优化控制实例，仿真结果表明了该算法对求解化工过程动态优化问题具有可行性和有效性。     

Trends in chemical engineering education: Process, product and sustainable chemical engineering challenges

Teaching chemical engineering has always been faced with a dilemma: either keep in touch with industry needs or incorporate new scientific concepts into the curriculum. In this paper, a short historical analysis of the evolution of chemical engineering teaching is presented and the recent trends of the two previous facets (industry and science) are briefly reviewed. The process vs product engineering concept is proposed as one of the means to achieve a better alignment between the curriculum and industry needs. A chemical engineering teaching framework, based in part on a product and a process oriented component, which has been in place in our department 5 years ago, is described and discussed. The concept of sustainable chemistry, including process and product considerations, which can be seen as the next frontier in chemical engineering education, is finally analysed from the education point of view.     

精细化工发展的关键技术--模型化、控制与优化研究

过程模型化、控制和优化技术已成为制约我国精细化工发展的瓶颈之一.分析了我国精细化工的现状、影响未来发展的主要因素、内在特性,及其对过程模型化、控制与优化研究的影响与需求,综述了精细化工过程模型化、控制和优化的国内外研究情况.指出了我国精细化工过程模型化、控制和优化研究的研究原则,并提出了相应的研究方案.     

CO2 methanation: Optimal start‐up control of a fixed‐bed reactor for power‐to‐gas applications

Utilizing volatile renewable energy sources (e.g., solar, wind) for chemical production systems requires a deeper understanding of their dynamic operation modes. Taking the example of a methanation reactor in the context of power‐to‐gas applications, a dynamic optimization approach is used to identify control trajectories for a time optimal reactor start‐up avoiding distinct hot spot formation. For the optimization, we develop a dynamic, two‐dimensional model of a fixed‐bed tube reactor for carbon dioxide methanation which is based on the reaction scheme of the underlying exothermic Sabatier reaction mechanism. While controlling dynamic hot spot formation inside the catalyst bed, we prove the applicability of our methodology and investigate the feasibility of dynamic carbon dioxide methanation. © 2016 American Institute of Chemical Engineers AIChE J, 63: 23–31, 2017     

State‐of‐the‐art and progress in the optimization‐based simultaneous design and control for chemical processes

Significant progress in the area of simultaneous design and control for chemical processes has been achieved and various methodologies have been put forward to address this issue over the last several decades. These methods can be classified in two categories (1) controllability indicator‐based frameworks that are capable of screening alternative designs, and (2) optimization‐based frameworks that integrate the process design and control system design. The major objective is to give an up‐to‐date review of the state‐of‐the‐art and progress in the challenging area of optimization‐based simultaneous design and control. First, motivations and significances of simultaneous design and control are illustrated. Second, a general classification of existing methodologies of optimization‐based simultaneous design and control is outlined. Subsequently, the mathematical formulations and relevant theoretical solution algorithms, their merits, strengths and shortcomings are highlighted. Last, based on the recent advances in this field, challenges and future research directions are discussed briefly. An attempt is made with the help of this review article to stimulate further research and disseminate the simultaneous design methods to challenging problem areas. In particular, the application of optimization‐based simultaneous design and control methods to large‐scale systems with highly inherent nonlinear dynamics often the case in industrial chemical processes remains a challenging task and yet to be solved. © 2012 American Institute of Chemical Engineers AIChE J, 58: 1640–1659, 2012     

先进控制条件下化工过程操作裕量与控制性能分析

引言化工过程的设计裕量可以定义为考虑过程不确定参数(包括工艺条件、设备条件、外来扰动)发生变化时为满足生产和操作要求需要在正常操作的标称设计值上增加的量。设计裕量根据其属性可以     

电镀清洗用水采用电导自控的必要、原理与困难

简述我国淡水资源的现状和分配使用,指出了电镀行业节水的紧迫性和现实困难.介绍了电导自动控水的原理及其在国内的应用情况.在以前专利产品的基础上进行重新设计和改进,以期制造出可靠性高、售价低的电导自动控水器,实现工业化生产.     

Integration of scheduling,design, and control of multiproduct chemical processes under uncertainty

The development of a methodology that addresses the simultaneous design, scheduling, and control of multiproduct processes is focused. The proposed methodology takes into account the influence of disturbances by the identification of their critical frequency, which is used to quantify the worst‐case variability in the controlled variables via frequency response analysis. The uncertainty in the demands of products has also been addressed by creating critical demand scenarios with different probabilities of occurrence, while the nominal stability of the system has been ensured. Two case studies have been developed as applications of the methodology. The first case study focuses on the comparison of classical semisequential approach against the simultaneous methodology developed, while the second case study demonstrates the capability of the methodology in application to a large‐scale nonlinear system. © 2015 American Institute of Chemical Engineers AIChE J, 61: 2456–2470, 2015     

A survey on applications of optimization-based integrating process design and control for chemical processes

Process design and control are closely related to each other in chemical engineering activities. Traditionally, process design and control system design are carried out in sequence. However, the integration of process design and control (IPDC) can bring greater economic benefits and process dynamic performance than traditional sequential design methods. This is true, particularly for modern chemical processes, in which various process units become more interacting and compact owing to the widespread use of heat integration and recycled streams, and the resulted impacts between process design and control begin to significantly influence both the capital and operational costs. Recently, considerable studies about the IPDC for chemical processes have been reported in published literature. The purpose of the paper is to survey the applications of optimization-based integrating process design and control for chemical processes. Firstly, attention has been focused on the applications of IPDC to different process units, for example, chemical reactors and separation columns. Then, the survey is extended to the applications of IPDC to plant-wide chemical processes. Finally, the future research challenges in the application of IPDC to chemical processes have been briefly discussed.     

Evaluation of the parameters used in iterative dynamic programming

To apply iterative dynamic programming (IDP) to optimal control problems having a very large number of control variables the use of randomly chosen values for control at each grid point is required. To gain insight into the effect of the number of allowable values for control, the region contraction factor, and the number of grid points for the state vector to be used, computational results are presented for two nonlinear systems, one of which possesses numerous local optima. The reliability of obtaining the global optimum for the bifunctional catalyst blend optimization problem was found to be somewhat higher by using randomly chosen values for control rather than by choosing the control values over a uniform distribution. The global optimum is obtained even when a small number of allowable values for control at each grid point and a small number of grid points for the states are used. There is a wide range of the region contraction factor for which rapid convergence to the optimum is obtained. Also the number of grid points for the state can be very small without adversely affecting convergence to the optimum.     

Effect of the choice of final time in optimal control of nonlinear systems

The choice of the final time, t_j, in the optimal control of nonlinear systems is shown to be very important. By choosing t_f to be small, and repeatedly optimizing the system operation over the short time intervals gives a highly oscillatory type of control for a particular nonlinear chemical reactor. The cumulative profit as compared to that obtained by choosing t_f to be large, is substantially lower. In the operation of a batch reactor it is shown that if t_f is small, bang-bang control with singular sub-arcs results. When t_f is large, the optimal control policy tends to be relatively smooth and the profitability is substantially improved.     

带有中间储罐的间歇精馏工艺动态控制模拟优化

甲酸甲酯-甲醇-水是化工生产过程中最常见的三元混合物之一。目前,间歇精馏工艺分离该三元混合物的研究较少,在动态控制方面也少有报道。本文研究了分离甲酸甲酯-甲醇-水的带有中间储罐的间歇精馏工艺动态控制模拟优化。利用Aspen Plus和Aspen Plus Dynamics软件,在稳态模拟的基础上,分别考察了液位控制结构和组分控制结构两种控制方案。结果表明,液位控制结构控制性能较差,达到稳定后甲醇和水的纯度较低。组分控制结构虽能提高产品纯度,但出现了较为严重的振荡现象。根据对组分控制结构的动态响应分析,本文提出了一种改进的组分控制结构,该控制结构能实现带有中间储罐的间歇精馏工艺的稳健控制,使各产品纯度得到提高。     

化工过程约束优化控制的可行性分析及约束处理

在化工领域过程控制中,普遍存在着各种对输出变量、输入变量甚至中间变量的约束。不同约束条件之间的矛盾会造成约束条件无法全部满足,优化控制器无可行解,给实际生产造成负面影响。从凸体几何角度,将化工生产过程中约束优化控制的可行性判定转化为凸多面体是否相交的问题,将不可行时合理的约束处理方案转化为一系列线性规划或非线性规划问题,提出无需人为参与的自动进行约束优化控制可行性分析和约束调整的算法。Shell公司提供的重油分馏塔典型案例实验证明,该算法能够在约束优化控制不可行时自动有效地进行合理的约束调整,超调量小,控制作用变化平缓,且有一定控制裕量。     

Safe model-based reinforcement learning for nonlinear optimal control with state and input constraints

Safety is a critical factor in reinforcement learning (RL) in chemical processes. In our previous work, we had proposed a new stability-guaranteed RL for unconstrained nonlinear control-affine systems. In the approximate policy iteration algorithm, a Lyapunov neural network (LNN) was updated while being restricted to the control Lyapunov function, and a policy was updated using a variation of Sontag's formula. In this study, we additionally consider state and input constraints by introducing a barrier function, and we extend the applicable type to general nonlinear systems. We augment the constraints into the objective function and use the LNN added with a Lyapunov barrier function to approximate the augmented value function. Sontag's formula input with this approximate function brings the states into its lower level set, thereby guaranteeing the constraints satisfaction and stability. We prove the practical asymptotic stability and forward invariance. The effectiveness is validated using four tank system simulations.     

Combination of multi-model predictive control and the wave theory for the control of simulated moving bed plants

In this work a new approach to the control of simulated moving bed (SMB) chromatographic separation processes is presented. This approach is based on the combination of the wave theory and Multi-Model Predictive Control (MMPC). The wave theory provides the theoretical framework in which the control law is formulated whereas receding-horizon MPC is used for determining the appropriate controller parameters. As SMB plants are distributed parameter systems (DPS) with nonlinearity arising from the expression of the adsorption isotherms, classical numerical methods for the solution of DPS are computationally demanding for MPC purposes. Reduced-order models are therefore derived using the proper orthogonal decomposition (POD) technique. To ensure stability, the POD model is updated on-line, resulting in MMPC.