Generalized multi-scale control scheme for cascade processes with time-delays

The cascade control is a well-known technique in process industry to improve regulatory control performance. The use of the conventional PI/PID controllers has often been found to be ineffective for cascade processes with long time-delays. Recent literature report has shown that the multi-scale control (MSC) scheme is capable of providing improved performance over the conventional PID controllers for processes characterized by long time-delays as well as slow RHP zeros. This paper presents an extension of this basic MSC scheme to cascade processes with long time-delays. This new cascade MSC scheme is applicable to self-regulating, integrating and unstable processes. Extensive numerical studies demonstrate the effectiveness of the cascade MSC scheme compared with some well-established cascade control strategies.     

Smart grid coordination in building HVAC systems: EMPC and the impact of forecasting

Energy consumption by heating, ventilation, and air conditioning (HVAC) systems exhibits a clear correlation with electricity prices. The method of economic model predictive control (EMPC) can be used in conjunction with thermal energy storage (TES) to time-shift power consumption away from periods of high demand to periods of low energy cost. Dynamic electricity pricing and weather condition forecasts can be readily incorporated within this methodology. Unfortunately, the receding horizon nature of this control strategy makes it very susceptible to the quality of the forecasts used. To this end, the development and implementation of several forecasting methods will be discussed. Finally, the EMPC performance of these methods will be assessed on a simple building example using active TES.     

A new calculation method of feedback controller gain for bilinear paper-making process with disturbance

This paper presents a new method to calculate the feedback control gain for a class of multivariable bilinear system, and also applied this method on the control of two sections of paper-making process with disturbance. The robust H∞ control problem is to design a state feedback controller such that the robust stability and a prescribed H∞ performance of the resulting closed-loop system are ensured. The controller turns out to be robust with respect to the disturbance in the plant. Utilizing the Schur complement and some variable transformations, the stability conditions of the multivariable bilinear systems are formulated in terms of Lyapunov function via the form of linear matrix inequality (LMI). The gain of controller will be calculated via LMI. Finally, the application examples of a headbox section and a dryer section of paper-making process are used to illustrate the applicability of the proposed method.     

A Dantzig–Wolfe decomposition algorithm for linear economic model predictive control of dynamically decoupled subsystems

This paper presents a warm-started Dantzig–Wolfe decomposition algorithm tailored to economic model predictive control of dynamically decoupled subsystems. We formulate the constrained optimal control problem solved at each sampling instant as a linear program with state space constraints, input limits, input rate limits, and soft output limits. The objective function of the linear program is related directly to the cost of operating the subsystems, and the cost of violating the soft output constraints. Simulations for large-scale economic power dispatch problems show that the proposed algorithm is significantly faster than both state-of-the-art linear programming solvers, and a structure exploiting implementation of the alternating direction method of multipliers. It is also demonstrated that the control strategy presented in this paper can be tuned using a weighted ℓ₁-regularization term. In the presence of process and measurement noise, such a regularization term is critical for achieving a well-behaved closed-loop performance.     

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.     

ECS-100 DCS控制系统在离子膜制碱装置中的应用

介绍某公司引进的离子膜制碱装置采用国产DCS系统的原由，系统的结构及特点。详细论述ECS-100 DCS在装置的特殊控制、顺序控制、联锁等方面的应用情况。     

前向树状紧急疏散网络的自适应性控制策略分析

针对前向树状的紧急疏散网络,提出了一种不需要进行需求预测且具有适应性和强鲁棒性的分散式控制疏散策略.通过分析如何确定典型匝道与快速路交汇点处的最优疏散路线,明确了构建可控疏散网络的基本原则.定义了前向树状紧急疏散网络,并对所构建网络的适用范围和具体风险水平标定处理作了明确说明.针对前向树状网络的典型子结构,给出了可以始终充分利用下游通行能力,且充分考虑上游来流具有较高风险水平特点的具体疏散路线选择及放流策略.在上述典型子结构分析基础上,给出了包括如何逆流向确定路段限制性通行能力、顺流向确定路段最大可行流量以及实时动态调整疏散策略等基本步骤的网络疏散策略.最后,通过一个数值算例,比较了新策略与纯粹上游优先策略、纯粹下游优先策略的运行效率,证明了新的适应控制策略的可行性与有效性.     

带速度控制的能量高效的数据收集算法

无线传感网络中, 在保证节点能耗较低, 从而延长网络寿命的基础上, 减小数据收集时延是数据收集的核心问题。为此, 提出了一种带速度控制的能量高效的移动数据收集方法。该方法首先基于节点剩余能量进行动态分簇, 每个簇形成两个簇头来分担簇头能耗; 然后给小车装载双天线, 使得节点能够MIMO数据上传; 最后利用TSP问题找到一条最优路径, 并对移动小车的速度进行控制, 以便小车能够更快地收集数据。仿真实验结果表明, 该方法能够均衡网络流量, 延长网络寿命; 与其他算法相比, 数据收集时延较短。     

流程加工CAN测控网络的应用层协议研究

为提高CAN测控网络的适应性和通信效率,以CAN2.0A技术规范为基础,针对流程加工测控网络的特点,设计面向流程加工领域的CAN总线应用层协议ProCAN。在明确流程加工概念及范围的基础上,分析流程加工测控系统结构模型的特征,提出通信报文的类型,定义标准数据帧仲裁域与数据域的编码格式,并讨论ProCAN协议的通信模式、通信状态、通信异常及长报文误帧重传控制。利用OPNET网络仿真软件进行实验,结果表明,ProCAN协议能实现报文通信,并且具有延时短、实时性强、可靠性高的特点,尤其当网络负载较大时,效果更为明显。