Practical-optimal control of a drum boiler power plant

Multivariable control of power plants has been studied by many researchers and also a number of practical applications have been presented in the last few years with the aim of improving the load following capabilities of thermal units. This paper summarizes the main results of an experimental application of optimal control to a drum boiler power plant at the Italian national electricity board. Referring to a previous work for the process model building, first a model reduction is performed with the main purpose of getting a simplified control structure. Then, an optimal regulator including feedforward and integral control is synthesized and some practical drawbacks of the synthesis are discussed with referrence to traditional control schemes leading to a reformulation of the optimal regulator which, while conserving optimality, exhibits a number of practical advantages and improved robustness against typical plant parameter variations. Since the motivation of the control structure reformulation is mostly derived from experimental results, field trials are reported where the performances of a well tuned coordinated control, of the classical optimal regulator and of the reformulated optimal control structure are compared. Perspectives of future industrial applications are briefly discussed in the conclusions.     

火电厂多代理控制系统

针对火电厂非线性、多变量和多控制目标的特点,设计了一个火电厂多代理控制系统(PPMACS).在PP MACS中,前馈控制代理(FFCAs)采用神经模糊系统进行决策,反馈控制代理(FBCAs)采用基于遗传算法的模糊系统进行决策.优化任务分解代理(OTDAs)通过一个优化代理和一个分解代理来进行多目标优化分解PPMACS的任务.协调代理根据运行条件协调PPMACS的各个代理.仿真结果显示了火电厂多代理控制系统能够实现火电单元机组的多目标运行和大范围负荷跟踪.神经网络、模糊逻辑和遗传算法是PPMACS中的智能代理进行决策的有效工具.     

基于DMC的循环流化床锅炉燃烧控制系统设计

循环流化床锅炉燃烧系统是一种纯滞后、大延迟、强耦合的系统。而多变量动态矩阵控制对模型精度要求不高,对惯性、延迟和耦合的适应能力较强,且有很强的鲁棒性,因此,把多变量动态矩阵控制用于循环流化床锅炉燃烧控制系统。仿真结果表明,该系统响应速度较快,输出量和控制量变化较小,取得了比较满意的控制效果。     

An algorithmic method for the selection of multivariable process control structures

In process systems, the selection of suitable sets of manipulated and controlled variables and the design of their interconnection, known as the control structure selection problem, is an important structural optimisation problem. The operating performance of a plant depends on the control structure selected as well as the characteristics of the disturbances acting on the plant. The economic penalty associated with the variability of main process variables close to active constraints is used in this work in order to develop a quantitative measure for the ranking of alternative control structures. Based on this measure, a general methodology is presented for the generation of promising control structures where general centralised, linear time invariant, output feedback controllers are used to form the closed loop system. The special case of optimal static output feedback controllers is further investigated in this paper. Furthermore, the problem of selecting proper weights in forming quadratic integral performance indices in designing optimal multivariable controllers is addressed. The validity and usefulness of the method is demonstrated through a number of case studies.     

热轧带钢层流冷却系统的前馈-反馈控制及其优化

以热轧层流冷却系统为研究对象,对如何提高带钢卷取温度控制精度进行了研究;在带钢冷却模型的基础上,对预设定模块进行了前馈补偿;考虑模型的不确定性和大时滞特性,采用模糊Smith预估器提高了反馈控制的精度;结果证明所采用的这些措施大大提高了卷取温度的控制精度。     

Multivariable adaptive control without a prior knowledge of the delay matrix

This paper is concerned with the structure and role of the time-delay matrix in discrete-time multivariable processes. Interpretations and properties of this matrix as a multivariable generalization of the SISO delay term are discussed. It is formally shown that a finite-time horizon or multi-step cost function for the multivariable case can be minimized subject to a suitable choice of output and control horizons and without prior knowledge of the system delay matrix.     

模糊复合控制方法在焦炉控制系统中的应用研究

针对焦炉温度的大惯性、纯滞后、非线性和时变性等特点。提出了一种新的模糊复合控制方法．它将常规的前馈控制、反馈控制与具有人工智能的模糊控制相结合。吸取了前馈控制改善系统动态响应特性、反馈控制消除稳态误差以及模糊控制能够较好地解决系统难以建立精确数学模型的优点。解决了焦炉温度控制问题．通过模糊复合控制的理论分析和仿真试验。证明了该控制方法的可行性和有效性．     

A neural network approach to freeway network traffic control

The paper investigates the application of a feedforward neural network approach to freeway network control via variable direction recommendations at bifurcation locations. A nonlinear control problem is formulated and solved first by use of computationally expensive nonlinear optimization techniques. A feedforward neural network is then trained by optimally adjusting its weights so as to reproduce the optimal control law for a limited number of traffic scenarios. Generalisation properties of the neural network are investigated and a discussion of advantages and disadvantages compared with alternative control approaches is provided.     

Probabilistic design of LPV control systems

This paper presents an alternative approach to design of linear parameter-varying (LPV) control systems. In contrast to previous methods, which are focused on deterministic algorithms, this paper is based on a probabilistic setting. The proposed randomized algorithm provides a sequence of candidate solutions converging with probability one to a feasible solution in a finite number of steps. The main features of this approach are as follows: (i) The randomized algorithm gives a method for general LPV plants with state space matrices depending on scheduling parameters in a nonlinear manner. That is, the probabilistic setting does not need a gridding of the set of scheduling parameters or approximations such as a linear fractional transformation of the state space matrices. (ii) The proposed algorithm is sequential and, at each iteration, it does not require heavy computational effort such as solving simultaneously a large number of linear matrix inequalities.     

An alternative to standard nuclear core control using a multi-objective approach

This paper proposes an alternative to standard nuclear core control. The control objectives are standard and concern the Average Coolant Temperature, the Axial Offset and the rod bank position (Pbank in this study). They were carefully formalized before proceeding to LTI structured controllers synthesis at various operating points, using a multi-objective approach. This study relies on a point kinetic core model, embedding an AO estimator. A Non-smooth optimization technique is used to solve the control problems at each operating point. Then gain scheduling is performed, taking advantage of the parsimonious parameterization of the considered multivariable controller. Finally, simulations are carried out on a highly realistic reactor model including a Xenon model and show the benefits of the new control     

鲁棒控制理论应用于宏观经济系统分析

针对宏观经济系统模型的不确定性，运用鲁棒控制理论进行宏观经济系统的分析与决策，使得宏观经济系统能够保持鲁棒稳定性并准确跟踪预先给定的目标。     

非线性倒立摆系统平衡点反馈控制参数的优化计算

本文基于圆轨倒立摆非线性系统模型,建立了平衡点状态反馈控制参数的高精度优化算法,编制计算程序确定出反馈控制参数,并对圆轨倒立摆平衡点的实例控制.与将系统线性化后的反馈参数的计算分析相比,本文研究方法具有较大平衡范围.仿真与实例平衡控制都表明了本文研究方法的可行性.     

改善室内环境舒适度的一种新型控制方法

室内环境舒适度直接影响着在室人员的健康和工作效率,需要进行有效的控制以保证其舒适性。论文以某办公室为研究对象,提出一种基于同策蒙特卡罗自适应控制方法对建筑物内空调系统、加湿器、除湿器、照明系统和通风系统等设备优化控制,调节室内温湿度、照度和CO₂浓度提高室内舒适感。建立了有关影响室内环境舒适度的因素的状态变化的数学模型,并利用实验数据验证模型,同时与PID和模糊控制算法进行了仿真对比分析。结果表明：在同时控制影响室内环境的多个因素时,同策蒙特卡罗控制方法能够较好的跟踪实际情况,且该方法稳态误差较小,收敛速度较快。     

Transfer matrix approach to the triangular block decoupling problem

The triangular block decoupling problem for linear multivariable systems is studied via the transfer matrix approach. This approach clearly separates the problem of admissible control laws from the one of desired decoupled system specifications. Necessary and sufficient triangular decoupling conditions are given for various control laws. These conditions are expressed in a very simple way in terms of linear dependance among the transfer matrix rows. It turns out that when the problem is solvable, this can be done by static state feedback on a minimal realization of the system. Furthermore it is shown that whenever triangular block decoupling is possible, it is also attainable with stability.     

鲁棒极点配置控制系统的一种设计方法

本文提出了系统特征系数灵敏度的概念,导出了特征系数灵敏度与特征值灵敏度闻的关系.在此基础上,提出了一种以加权特征系数灵敏度为性能指标,结构化小参数摄动下的鲁棒极点配置控制系统的设计方法.特征系数灵敏度计算简单,目标函数的极小化采用标准的具有二次收敛性质的参数最优化方法.     

多组合设备的调度控制研究综述

在半导体芯片制造中越来越广泛使用多组合设备.本文介绍了多组合设备的结构配置、生产运行过程、调度控制问题的一般特征条件、应该满足的约束及周期性调度策略;分析了问题的复杂性因素.从多组合设备的结构特征、运行过程特征两方面分类综述了调度问题的建模、分析方法、调度算法及存在的问题,最后指出了未来的研究方向.     

Gain scheduled control of linear systems with unsymmetrical saturation actuators

The problem of stabilisation of a class of nonlinear continuous-time systems with asymmetric saturations on the control is studied in this paper. By combining the parametric Lyapunov equation approach and gain scheduling technique, a state feedback gain scheduling controller is proposed to solve the stabilisation problem of systems with unsymmetrical saturated control. The proposed gain scheduled approach is to increase the value of the design parameter so that the convergence rate of the closed-loop system can be increased. Numerical simulations show the effectiveness of the proposed approach.     

Output feedback control of a class of feedforward nonlinear systems in the presence of sensor noise

We propose an output feedback controller for a class of feedforward nonlinear systems under sensor noise. The sensor noise is any signal whose DC component is finite, which covers not only deterministic signals but also random signals including many practical noises. We introduce a notion of virtual state, then propose a measurement output feedback controller that utilizes a gain scaling factor. The gain scaling factor is commonly employed by the observer and controller. Through analysis, we show that all system states and output remain to be bounded in the presence of sensor noise, and the bound of states except output can be made arbitrarily small. Moreover, if the DC component of sensor noise is zero, the ultimate bound of the states and output can be made arbitrarily small by increasing the gain scaling factor in the presence of sensor noise. Copyright © 2013 John Wiley & Sons, Ltd.     

Bounded control of feedforward nonlinear systems subject to input time‐delay

This article is concerned with the global stabilization problem of a family of feedforward nonlinear time‐delay systems whose linearized system consists of multiple distinct oscillators. To fully utilize the delayed information and maintain the state decoupling property in the controller design, the considered nonlinear feedforward system is first transformed into a new system which contains time delays in both its input and states based on a novel model transformation containing time delays, and then the stabilizing saturated controller for the transformed system is designed based on the recursive design method. Meanwhile, explicit stability conditions are also provided. When the linearized system is a cascade of multiple oscillators and multiple integrators, a modified saturated feedback control utilizing not only the current state but also the delayed state is also established for the corresponding global stabilization problem. Two examples, including a practical one, are given to show the effectiveness and superiority of the proposed approaches.     

Optimization of train-speed trajectory and control for mass rapid transit systems

This paper presents a method to optimize the train-speed trajectory and control between successive stations for mass rapid transit systems with the cable signaling system. The MAX-MIN ant system is utilized to search for the optimal speed codes of each section while taking track gradient, average speed, restriction of train speed, acceleration and jerk into consideration. The train acceleration is further regulated by a fuzzy-PID gain scheduler to meet the speed commands determined. Satisfactory simulation results show applicability and effectiveness of the proposed approach as a tool for designing an energy-saving mass rapid transit system.