基于微机的200Wm的核供热堆仿真系统PCNHR1．0的研究

为了使更多的技术人员形象地了解低温堆供热站的原理，在国际原子能机构的支持下，清华大学核研究研究开发了基于微机的200M低温核供堆仿真系统。它采用两回路、一维漂移热工水力学模型，点中子堆物理以及控制系统模型。能对核供热堆的稳态发行、瞬态过程和事故进行仿真，仿真精度接近系统分析结果。在奔腾或以上的微机上，WINDOWS95／98／NT操作系统下，能对过程进行仿真实仿真，而且大多数过程能达到10倍以上超实时，软件采用VisualC 和FORTRAN混合语言编程，运用先进的多线程编程模型，进程通讯和进程控制技术实现了耦合计算和同步控制。     

可编程序控制器在核供热堆控制棒逻辑控制系统中的应用

介绍了基于可编程序控制器的核供热堆控制棒逻辑控制系统模型。详细地介绍了核供热堆棒控制系统的功能及实现方法。通过对该系统的整体结构的分析,在易于扩展的前提下,对控制棒选择中的互锁算法进行了讨论,并进一步探讨了在可编程序控制器的开发过程中的时序问题。     

可编程控制器在核供热堆报警系统中的应用

介绍一种用可编程序控制器构成的核供热堆报警系统.具体介绍了核供热堆报警参数的分类,报警系统的功能、硬件构成、报警逻辑设计以及编程中关键技术问题.     

热离子空间堆控制系统研究

空间堆与传统地面反应堆的运行特性和控制方式不同，研究空间堆的控制系统十分必要。基于Matlab&Simulink工具箱，建立了热离子空间堆仿真模型。建立的模型包括点堆中子动力学模型、热工水力模型和热电转换模型。基于热离子空间堆仿真模型，建立了核功率、电功率以及冷却剂出口温度控制系统，并进行了控制参数整定和仿真分析。对电功率和冷却剂出口温度控制系统进行了优化，设计了串级控制系统。仿真结果表明：选用核功率作为被控量的控制系统控制效果较好；选用电功率和冷却剂出口温度作为被控量的控制系统控制效果较差；核功率的超调量较大。使用串级控制器优化后，控制性能得到了显著的提升。     

MATLAB 和VC ++联合编程的COM 研究

VC+ +在实现矩阵运算、数值分析、工程计算等方面比较复杂,应用VC+ + 与MATLAB 混合编程方法可以充分发挥VC+ + 和MATLAB 各自优势,提高仿真和开发效率。着重介绍了利用组件对象模型(COM) 技术的VC+ + 与MATLAB 的联合编程方法,阐述了该方法实现过程,并通过两个具体应用实例加以验证。实验仿真结果表明,采用联合编程的COM 技术能快速直观地得到满意结果,对求解矩阵运算、数值分析、工程计算等问题是行之有效的。     

电力变压器的动态数字实时仿真模型

在电力系统动态数字实时仿真研究中,变压器模型应该被精确描述。文中提出了一个三相、双绕组、Y0/△-11电力变压器(由3个单相变压器组成)的数字实时仿真模型,对该变压器空载合闸的合闸涌流的电磁暂态过程及匝间短路故障运行过程进行了仿真。仿真实例在PC机系统上的运行结果表明,所提出的模型和选用的数字积分方法是正确的,并且能实时实现。     

电力变压器的动态数字实时仿真模型

在电力系统动态数字实时仿真研究中,变压器模型应该被精确描述.文中提出了一个三相、双绕组、Y0/△-11电力变压器(由3个单相变压器组成)的数字实时仿真模型,对该变压器空载合闸的合闸涌流的电磁暂态过程及匝间短路故障运行过程进行了仿真.仿真实例在PC机系统上的运行结果表明,所提出的模型和选用的数字积分方法是正确的,并且能实时实现.     

AMESim液压系统模型实时仿真研究

为了研究AMESim液压模型实时仿真,建立一个简单的液压模型,生成非托管动态链接库,并基于C#语言进行编程。通过对模型在AMESim软件环境下的非实时仿真和在windows应用程序下的实时仿真作比较,结果表明,该系统成功实现了AMESim液压模型的实时仿真。     

Linux环境下模型直升机飞行过程的实时3D仿真

论文给出了模型直升机飞行仿真系统的整体结构。介绍了在Linux平台下,采用FLTK图形界面库和Mesa/OpenGL实现模型直升机飞行状态3D可视化仿真与实时再现的过程,并分析了仿真过程中建模、动画显示、网络通讯、视角变换等问题。     

机器人图形示教盒编程的研究

本文介绍机器人作业的图形示教盒编程.通过建立机器人的运动学和三维几何模型,采用实时动画技术,在计算机屏幕上对机器人进行图形仿真示教,文中还讨论了图形示教程序的单步执行和实时修正方法,并给出了国产 PJ-lA 机器人进行喷漆作业的图形示教盒编程的实例.结果表明:机器人的图形示教盒编程具有生动、方便的特点,为机器人的编程研究提供了适用的工具.     

Nonlinear observer based control for travelling wave nuclear reactors based on the Lyapunov approach during load following operation

Power control of the nuclear reactor is one of the most important subjects in each nuclear power plant. In this paper, a nonlinear controller using sliding mode method which is a robust nonlinear controller is designed to control a Traveling Wave Nuclear Reactor (TWR) power. The reactor core is simulated based on the point kinetics equations and six delayed neutron groups. Considering the limitations of the delayed neutron precursors densities measurement, a sliding mode observer is designed to estimate their values and finally a sliding mode control based on the sliding mode observer is presented to control the reactor core power. The stability analysis is given by means Lyapunov approach, thus the control system is guaranteed to be stable within a large range. Sliding Mode Control (SMC) is one of the robust and nonlinear methods which have several advantages such as robustness against matched external disturbances and parameter uncertainties. Since it has systematic design procedure, it is one of the most powerful solutions to design many practical control systems. The designed control system is evaluated in the presence of disturbances and uncertainties. The results show the robustness and performance of the used control system.     

A case study and troubleshooting experience of safety power channel of instrumentation and control system of the BAEC TRIGA Research Reactor

Microsystem Technologies - Bangladesh Atomic Energy Commission TRIGA Research Reactor (BTRR) is a MK II type nuclear research reactor with a maximum thermal output power of 3 MW. Nuclear...     

基于RELAP5的沸水堆机理模型建立与仿真

核电厂高精度、实时、动态仿真要求有准确的反应堆热工水力以及控制系统等模型,它除用于电厂安全分析、操纵员培训等,还可用于控制系统参数优化、实际仪表控制系统验证等方面。为了研究在核电站控制系统问题上引入智能控制和优化算法的可行性,利用热工水力软件RELAP5,以沸水堆核电站为例,对沸水堆的堆芯系统和主给水系统进行了建模,并在稳态和暂态工况下进行了仿真验证。仿真结果与电站的实际数据基本一致,表明了基于RELAP5程序所建立的沸水堆热工水力模型的正确性。     

Implementation of Adaptive Fuzzy Control for a Real-Time Control Demo-Model

From 1995–1999 a R&D project on fuzzy control applications to the Belgian Reactor 1 (BR1) was conducted at the Belgian Nuclear Research Centre (SCK·CEN). Due to the safety regulations of the nuclear reactor, it is not realistic to perform many experiments at BR1. In this situation, part of the pre-processing experiments had to be carried outside the reactor (e.g., comparisons of different methods and the preliminary choices of the parameters). Therefore a water-level control system, referred to as a real-time control demo-model, was designed and constructed. In this paper, the construction of the demo-model and related hardware aspects is firstly outlined, then the results of a fuzzy control (Mamdani-type) and an adaptive fuzzy control are presented. The adaptive fuzzy control is a fuzzy control with an adaptive function that can self-regulate the fuzzy control rules. Finally, an implementation of a computer simulation is introduced with an adaptive fuzzy control for this real-time control demo-model.     

An algorithm for non-linear space—Time nuclear reactor control

A novel multivariable control algorithm for non-linear space-time nuclear reactor dynamics is proposed in this paper. The multivariable control algorithm is based on a mathematical model of the nuclear reactor which includes: a single energy group of neutrons, delayed neutron precursors, iodine, xenon and thermal-hydraulic feedback. The multivariable control algorithm is composed of non-linear time-varying feedforward and feedback control signals, a reference model of the nuclear reactor and a dynamic observer. The non-linear proportional plus integral feedback controller forces the nuclear reactor to follow the response of the reference model. The dynamic observer estimates the unmeasurable state variables. The feedforward and feedback control signals are determined in a novel approach by specifying the form of the closed-loop response of the neutron density variables. By virtue of the multivariable control algorithm the closed-loop differential equations are linear and time-varying. A linear stability analysis for base-load and load-cycle operation indicates that the closed-loop system is stable provided that the thermal-hydraulic subsystem is inherently stable. The simulated dynamic response indicates that the multivariable control algorithm provides excellent response characteristics.     

A pulp mill benchmark problem for control: problem description

This work introduces a benchmark problem of a pulping process, including both the fiber line and the chemical recovery area. The complete details of the pulp mill process are presented, including the control objectives, modes of operation, process constraints, measurements and costs. The dynamic model, including the source/binary code of all the unit operations is made available to the academic community as a benchmark for use in process system engineering studies.     

An experimentally validated simulation model for a four-stage spray dryer

In this paper, we develop a dynamic model of an industrial type medium size four-stage spray dryer. The purpose of the model is to enable simulations of the spray dryer at different operating points, such that the model facilitates development and comparison of control strategies. The dryer is divided into four consecutive stages: a primary spray drying stage, two heated fluid bed stages, and a cooling fluid bed stage. Each of these stages in the model is assumed ideally mixed and the dynamics are described by mass- and energy balances. These balance equations are coupled with constitutive equations such as a thermodynamic model, the water evaporation rate, the heat transfer rates, and an equation for the stickiness of the powder (glass transition temperature). Laboratory data is used to model the equilibrium moisture content and the glass transition temperature of the powder. The resulting mathematical model is an index-1 differential algebraic equation (DAE) model with 12 states, 9 inputs, 8 disturbances, and 30 parameters. The parameters in the model are identified from well-excited experimental data obtained from the industrial type spray dryer. The simulated outputs of the model are validated using independent well-excited experimental data from the same spray dryer. The simulated temperatures, humidities, and residual moistures in the spray dryer compare well to the validation data. The model also provides the profit of operation, the production rate, the energy consumption, and the energy efficiency. In addition, it computes stickiness of the powder in different stages of the spray dryer. These facilities make the model well suited as a simulation model for comparison of the process economics associated to different control strategies.     

Adaptive neural model-based fault tolerant control for multi-variable processes

An adaptive neural network model-based fault tolerant control approach for unknown non-linear multi-variable dynamic systems is proposed. A multi-layer Perceptron network is used as the process model and is adapted on-line using the extended Kalman filter to learn changes in process dynamics. In this way, the adaptive model will learn the post-fault dynamics caused by actuator or component faults. Then, the inversion of the neural model is used as a controller to maintain the system stability and control performance after fault occurrence. The convergence of the model inversion control is proved using Lyapunov method. The proposed method is applied to the simulation of a two-input two-output continuous-stirred tank reactor to demonstrate the effectiveness of the approach. Several actuator and component faults are simulated on the continuously stirred tank reactor process when the system is under the proposed fault tolerant control. The results have shown a fast recovery of tracking performance and the maintained stability.     

Modeling and control of a novel heat exchange reactor,the Open Plate Reactor

A new chemical reactor, the Open Plate Reactor, is being developed by Alfa Laval AB. It combines good mixing with high heat transfer capacity into one operation. With the new concept, highly exothermic reactions can be produced using more concentrated reactants. A nonlinear model of the reactor is derived and a control system is developed. For temperature control a cooling system is designed and experimentally verified, which uses a mid-ranging control structure to increase the operating range of the hydraulic equipment. A Model Predictive Controller is proposed to maximize the conversion under hard input and state constraints. An extended Kalman filter is designed to estimate unmeasured concentrations and parameters. Simulations show that the designed control system gives high conversion and ensures that the temperature inside the reactor does not exceed a pre-defined safety limit.     

Adaptation of diagonal recurrent neural network model

An adaptive direct recurrent neural network model is developed for nonlinear dynamic system modelling in this paper. The model adaptation is achieved with the extended Kalman filter (EKF). A novel recursive algorithm is proposed to calculate the Jacobian matrix in the model adaptation so that the algorithm is simple and converges fast. The effectiveness of the developed adaptive model is demonstrated by applying to modelling a simulated continuous stirred tank reactor (CSTR). The model converges to the new process dynamics very quickly after a constant disturbance is added, and therefore can be used as an adaptive model in the adaptive model predictive control or internal model control for time-varying systems or fault tolerant control of nonlinear systems.