A model structure-driven hierarchical decentralized stabilizing control structure for process networks

Based on the structure of process models a hierarchically structured state-space model has been proposed for process networks with controlled mass convection and constant physico-chemical properties. Using the theory of cascade-connected nonlinear systems and the properties of Metzler and Hurwitz matrices it is shown that process systems with controlled mass convection and without sources or with stabilizing linear source terms are globally asymptotically stable. The hierarchically structured model gives rise to a distributed controller structure that is in agreement with the traditional hierarchical process control system structure where local controllers are used for mass inventory control and coordinating controllers are used for optimizing the system dynamics. The proposed distributed controller is illustrated on a simple non-isotherm jacketed chemical reactor.     

Optimal Process Control Using Neural Networks

Infinite time optimal controllers have been designed for a dispersion type tubular reactor model by using the framework of adaptive critic optimal control design. For the reactor control problem, which is governed by two coupled nonlinear partial differential equations, an optimal controller synthesis is presented through two sets of neural networks. One set of neural networks captures the relationship between the states and the control, whereas the other set of networks captures the relationship between the states and the costates. This innovative approach embeds the solutions to the optimal control problem for a large number of initial conditions in the domain of interest. Although the main aim of this paper is to solve a process control problem, the methodology presented here can be viewed as a practical computational tool for many problems associated with nonlinear distributed parameter systems. Numerical results demonstrate the viability of the proposed method.     

基于PCS7的多容器控制系统设计

以工业中常见的反应器、闪蒸罐等所组成的多容器为被控对象,分析工艺流程和控制指标要求。结合过程控制实训系统(SMPT 1000),设计了多容器控制系统方案。通过PCS7的顺序功能图(SFC)实现自动开车流程,连续功能图(CFC)搭建控制回路。针对反应器进出口流量、反应器温度、反应器液位和闪蒸罐压力,分别进行单回路或复杂控制,使其在安全、稳定的状态下高效产出反应物。尤其是针对连续生产过程中多个容器的生产工艺关联性问题,从反应器进、出料的动态平衡出发,设计了反应器的进料流量控制。控制结果表明,该反应器控制系统的方案设计合理、运行稳定可靠、生产效率高,达到了生产指标要求。该研究对基于PCS7的连续过程控制系统在工程应用和试验具有一定的参考价值。     

Decentralized control of the Tennessee Eastman Challenge Process

A decentralized control system is developed for the Tennessee Eastman Challenge Process (TE problem). The design procedure begins with the selection of the method for production-rate control, to which inventory controls and other functions are then coordinated. Results show that production rate can be maximized at any of the three standard product compositions, even when the feed of reactant A is lost. All specifications of the challenge problem are satisfied despite large disturbances in feed composition and reaction kinetics. Variability in product rate and quality is less than that seen in previous studies. The process can operate on-spec for long periods without feedback from composition measurements. Setpoints for certain variables (such as reactor temperature and concentrations of A and C in the reactor feed) must be chosen a priori, and the effect on operating cost is estimated. The performance of the proposed decentralized control is compared to that of a nonlinear model predictive control (NMPC) developed previously. There appears to be little, if any, advantage to the use of NMPC in this application. In particular, the decentralized strategy does a better job of handling constraints - an area in which NMPC is reputed to excel. Reasons for this are discussed.     

A comprehensive analytical model of interconnection networks in large‐scale cluster systems

The trends in parallel processing system design and deployment have been toward networked distributed systems such as cluster computing systems. Since the overall performance of such distributed systems often depends on the efficiency of their communication networks, performance analysis of the interconnection networks for such distributed systems is paramount. In this paper, we develop an analytical model, under non‐uniform traffic and in the presence of communication locality, for the m‐port n‐tree family interconnection networks commonly employed in large‐scale cluster computing systems. We use the proposed model to study two widely used interconnection networks flow control mechanism namely the wormhole and store&forward. The proposed analytical model is validated through comprehensive simulation. The results of the simulation demonstrated that the proposed model exhibits a good degree of accuracy for various system organizations and under different working conditions. Copyright © 2007 John Wiley & Sons, Ltd.     

LQ optimal and reaching law-based sliding modes for inventory management systems

In this article, the theory of discrete sliding-mode control is used to design new supply strategies for periodic-review inventory systems. In the considered systems, the stock used to fulfil an unknown, time-varying demand can be replenished from a single supply source or from multiple suppliers procuring orders with different delays. The proposed strategies guarantee that demand is always entirely satisfied from the on-hand stock (yielding the maximum service level), and the warehouse capacity is not exceeded (which eliminates the cost of emergency storage). In contrast to the classical, stochastic approaches, in this article, we focus on optimising the inventory system dynamics. The parameters of the first control strategy are selected by minimising a quadratic cost functional. Next, it is shown how the system dynamical performance can be improved by applying the concept of a reaching law with the appropriately adjusted reaching phase. The stable, nonoscillatory behaviour of the closed-loop system is demonstrated and the properties of the designed controllers are discussed and strictly proved.     

Neural Network Structures for Optimal Control of LPCVD Reactors

In this paper, a new approach of LPCVD reactor modelling and control is presented, based on the use of neural networks. We first present the development of a hybrid networks model of the reactor. The objective is to provide a simulation model which can be used to compute online the film thickness on each wafer. In the second section, the thermal control of a LPCVD reactor is studied. The objective is to develop a multivariable controller to control a space- and time-varying temperature profile inside the reactor. A neural network is designed using a methodology based on process inverse dynamics modelling. Good control results have been obtained when tracking space-time temperature profiles inside the LPCVD reactor pilot plant. Finally, global software is elaborated to achieve film thickness control in an experimental LPCVD reactor pilot plant, in order to get a defined and uniform deposition thickness on the wafers all along the reactor. Experimental results are presented which confirm the efficiency of the optimal control strategy.     

Adaptive control Lyapunov function based model predictive control for continuous nonlinear systems

A design of adaptive model predictive control (MPC) based on adaptive control Lyapunov function (aCLF) is proposed in this article for nonlinear continuous systems with part of its dynamics being unknown at the starting time. Specifically, to guarantee the convergence of the closed-loop system with online predictive model updating, a stability constraint is designed. It limits the aCLF of the system under the MPC to be less than that under an online updated auxiliary adaptive control. The auxiliary adaptive control which implements in a sampling-hold fashion can guarantee the convergence of the controlled system. The sufficient conditions that guarantee the states to be steered to a small region near the equilibrium by the proposed MPC are provided. The calculation of the proposed algorithm does not depend on the model mismatch at the starting time. And it does not require the Lyapunov function of the state of the real system always to be reduced at each time. These provide the potential to improve the performance of the closed-loop system. The effectiveness of the proposed method is illustrated through a chemical process example.     

含时滞的不确定性供应链网络系统牛鞭效应控制策略及其经济性能分析

考虑需求、生产能力、供应链结构等内外不确定性因素和供应链系统运作延迟,构建了不确定环境下含时滞的供应链库存网络系统状态转移模型.针对牛鞭效应问题,提出了基于库存水平波动状态的控制策略和相应的经济性能指标;借助线性矩阵不等式方法,深入分析库存策略的参数优化设计对牛鞭效应以及经济性能的影响.仿真结果表明,在经济性能约束下,该库存策略具有较强的牛鞭效应遏制能力,从而表明了策略的有效性和实用性.     

带滤波的无线传感器网络的H∞控制

本文研究了基于滤波的无线传感器网络的H∞控制问题.首先建立了无线传感器网络的模型,然后使用稳态Kalman滤波器对多个传感器节点的输出信号进行滤波,将滤波后的信号作为无线传感器网络系统的反馈输出,并通过建模和分析得到带干扰的线性离散切换系统模型.最后设计了切换控制器,并基于Lyapunov函数给出了在任意切换条件下使该切换系统满足H∞控制的条件.仿真结果验证了该方法和结果的可行性.     

基于非线性系统T-S模糊模型的随机最小方差控制

以非线性系统的T-S模糊模型为基础,提出了一种基于最小方差性能指标的随机控制方法。分析了系统的稳定性问题并给出了系统稳定的充分条件。将此方法用于连续反应搅拌釜(CSTR)中和过程pH值控制的仿真试验,仿真结果表明了该方法的有效性。     

Nonlinear adaptive control using neural networks and its application to CSTR systems

In this paper, adaptive tracking control is considered for a class of general nonlinear systems using multilayer neural networks (MNNs). Firstly, the existence of an ideal implicit feedback linearization control (IFLC) is established based on implicit function theory. Then, MNNs are introduced to reconstruct this ideal IFLC to approximately realize feedback linearization. The proposed adaptive controller ensures that the system output tracks a given bounded reference signal and the tracking error converges to an -neighborhood of zero with being a small design parameter, while stability of the closed-loop system is guaranteed. The effectiveness of the proposed controller is illustrated through an application to composition control in a continuously stirred tank reactor (CSTR) system.     

基于模糊控制律的遗传神经匝道协调控制

讨论了快速路匝道系统中智能控制技术问题。针对匝道系统特点,分析了模糊控制、人工神经网络、遗传算法的适用性,提出了一种基于模糊控制律的遗传神经匝道协调控制方案。在该方案中,对模糊控制输入输出数据进行线性修正,使用修正后的数据完成遗传神经网络训练,并用神经网络代替模糊控制器对匝道系统进行控制。给出了神经网络结构和遗传算法流程,并结合宏观交通流模型进行系统仿真。仿真结果表明,与模糊控制相比,控制效果显著提高。     

不确定离散时滞网络化系统的鲁棒H∞控制

研究了不确定离散时滞网络系统的鲁棒H∞控制问题。在假设数据丢失过程是一个独立同分布过程的情况下,运用随机Lyapunov函数方法,得到了网络化系统均方渐近稳定且满足给定H∞性能指标的充分条件,并利用线性矩阵不等式方法给出镇定控制器的设计,仿真表明该方法的有效性。     

有界扰动下约束非线性系统鲁棒经济模型预测控制EI北大核心CSCD

针对未知但有界扰动下约束非线性系统,提出一种新的鲁棒经济模型预测控制(Economic model predictive control,EMPC)策略,保证闭环系统对扰动输入具有输入到状态稳定性(Input-to-state stability,ISS).基于微分对策原理,分别优化经济目标函数和关于最优经济平衡点的鲁棒稳定性目标函数,其中经济最优性与鲁棒稳定性是具有冲突的两个控制目标.利用鲁棒稳定性目标最优值函数构造EMPC优化的隐式收缩约束,建立鲁棒EMPC的递推可行性和闭环系统关于最优经济平衡点相对于有界扰动输入到状态稳定性结果.最后以连续搅拌反应器为例,对比仿真验证本文策略的有效性.     

Design and control of an ethyl acetate process: coupled reactor/column configuration

In this paper, design and control of a realistic coupled reactor/column process to produce ethyl acetate is studied. The process design is more complicated because the ethyl acetate product is neither the lightest nor the heaviest component in the system. A search procedure is proposed to obtain the optimum process design and operating condition of this process. The optimum process design is the one that minimize the Total Annual Cost (TAC) of this process while satisfying the stringent product impurity specifications. The optimum overall process design includes a continuous-stirred tank reactor (CSTR) coupled with a rectifier, a decanter, another stripper, and a recycle stream. After the process design is established, the next step is to use dynamic simulation to test the appropriate control strategy for this process. Sensitivity analysis is performed to obtain the suitable temperature control points for the columns. The proposed control strategy is very simple containing only one temperature control loop in each column. This recommended simpler control strategy uses the ratio of acetic acid feed rate to ethanol feed rate to control the 5th stage temperature of the rectifier and uses the stripper reboiler duty to control the 5th stage temperature of the stripper. The proposed control strategy does not need any on-line composition measurements and can properly hold product purity in spite of feed flow rate and feed composition disturbances. For small deviations of the product impurity compositions during disturbances, a slow cascade outer composition loop structure can be implemented using off-line composition measurements from the quality lab.     

Quadratic stabilization of linear networked control systems via simultaneous protocol and controller design

We derive conditions for quadratic stabilizability of linear networked control systems by dynamic output feedback and communication protocols. These conditions are used to develop a simultaneous design of controllers and protocols in terms of matrix inequalities. The obtained protocols do not require knowledge of controller and plant states but only of the discrepancies between current and the most recently transmitted values of nodes’ signals, and are implementable on controller area networks. We demonstrate on a batch reactor example that our design guarantees quadratic stability with a significantly smaller network throughput than previously available designs.     

On the control of non-linear processes: An IDA–PBC approach

A high performance non-linear controller that exploits the properties of port-Hamiltonian systems to precisely define the interconnections and energy dissipations of non-linear processes is presented for a large class of chemical processes. The controller is derived from classical interconnection and damping assignment–passivity based control theory but an additional degree of freedom is introduced in the controller design by the use of “non-exact matching” closed-loop storage functions. By a proper closed-loop interconnection assignment the proposed controller achieves total decoupling between outputs and since no inversion of the process dynamics is made in the design it is equally applicable to minimum phase and nonminimum phase system. The controller design methodology is presented and stability conditions are stated. As illustrative example the proposed method is used to design controllers for a multiple-input/multiple-output non-isothermal continued stirred tank reactor that exhibits nonminimum phase behavior.     

Stabilization of an unstable tubular reactor by nonlinear passive output feedback control

The multiple–input multiple–output (MIMO) output feedback (OF) control problem of an exothermic multi-jacket tubular open-loop unstable reactor is addressed. Over its axial length, the reactor has several equally sized cooling jackets. The controller must adjust the jacket temperatures on the basis of per jacket temperature measurements so that the closed-loop system is robustly stable. The problem is solved within a constructive framework, by combining notions and tools from chemical reactor engineering and partial differential equations (PDEs) control systems theory. The result is a MIMO nonlinear OF dynamic control design with (i) a decentralized MIMO passive state feedback (SF) controller implemented with a pointwise observer (PWO), (ii) closed-loop stability conditions in terms of sensor set and control gains, and (iii) efficient late lumping-based on-line implementation. The design is put in perspective with industrial PI and inventory control, and applied to a representative example through numerical simulation with favorable comparison against adaptive controllers.