Gain scheduled dynamic sliding mode control for nuclear steam generators

U-Tube Steam Generator (UTSG) is one of the most important facilities in a pressurized-water nuclear reactor. Poor control of the Steam Generator (SG) water level in the secondary circuit of a nuclear power plant can lead to frequent reactor shutdowns or damage of turbine blades. The control problem is challenging, especially at low power levels due to shrink and swell phenomena and flow measurement errors. In addition, the dynamics of steam generator vary as the power level changes. Therefore, designing a suitable controller for all power levels is a necessary step to enhance the plant availability factor. The purpose of this paper is to design, analyze and evaluate a water level controller for U-tube steam generators using dynamic sliding mode control. The employed method is easy to implement in practical applications and moreover, the dynamic sliding mode control exhibits the desired dynamic properties during the entire output-tracking process independent of perturbations. Gain scheduling is used to obtain a global water level controller. Simulation results are presented to demonstrate the performance, robustness, and stability of the proposed controller.Computer simulations show that the proposed controller improves the transient response of steam generator water level and demonstrates its superiority to existing controllers.     

Application of a neural network based feedwater controller to helical steam generators

In current generation pressurized water reactors (PWRs), the control of steam generator level experiences challenges over the full range of plant operating conditions. These challenges can be particularly troublesome in the low power range where the feedwater is highly subcooled and minor changes in the feed flow may cause oscillations in the SG level, potentially leading to reactor trip. The IRIS reactor concept adds additional challenges to the feedwater control problem as a result of a steam generator design where neither level or steam generator mass inventory can be measured directly.Neural networks have demonstrated capabilities to capture a wide range of dynamic signal transformation and non-linear problems. In this paper a detailed engineering simulation of plant response is used to develop and test neural control methods for the IRIS feedwater control problem. The established neural network mass estimator has demonstrated the capability to predict the steam generator mass under transient conditions, especially at low power levels, which is considered the most challenging region for a full range feed water controller.     

Data-driven controller of nuclear steam generators by set membership approximation

Poor control of U-tube steam generators (UTSG) in a nuclear power plant can lead to frequent reactor shutdowns or damage of turbine blades. The steam generator is a highly complex, non-linear and time-varying system and its parameters vary with operating conditions. Therefore, it seems that design of a suitable controller is a necessary step to enhance plant availability factor. In this paper, a data-driven controller approximated by set membership approach is presented for the water-level control of U-tube steam generators in nuclear power plants. This controller is capable of learning the control action principles from the data obtained using other methods of automatic or manual control. Simulation results of the approximated controller demonstrate its capability in regulating the water level under random disturbances and reference level changes.     

Adaptive fuzzy model based predictive control of nuclear steam generators

Poor control of U-tube steam generators (UTSG) in a nuclear power plant can lead to frequent reactor shutdowns or damage of turbine blades. The dynamics of steam generator vary as power level changes. There is, therefore, a need to systematically design a suitable controller for all power levels. In this paper, we employ the concepts of both predictive control and fuzzy set theory to design an appropriate control for UTSG water level. The controller has three main parts: (1) a TSK fuzzy model used for predicting the future behavior of UTSG, (2) a recursive algorithm to estimate parameters of this model and (3) a model predictive controller used to obtain optimal input control sequence. Simulation results show that the proposed controller has a remarkable performance for tracking the step and ramp reference trajectories while at the same time it is robust against steam flowrate changes.     

基于SPSA的蒸汽发生器液位MPC系统性能优化方法研究

核电厂蒸汽发生器（SG）液位变化过程具有强非线性且存在“虚假水位”现象,传统SG液位控制系统多采用固定参数比例-积分-微分（PID）控制器,但传统PID控制方法不具备自优化、自适应、自学习等能力,使得控制系统性能难以达到并保持最佳。为提高机组瞬态响应能力以及核电厂的稳定性、安全性和经济性,提出了一种基于并行摄动随机逼近（SPSA）算法的模型预测控制（MPC）方法。该方法采用MPC系统代替传统PID控制系统,并利用SPSA实现液位控制系统参数的整定优化,从而实现SG液位控制系统的性能优化。通过仿真试验验证了本方法能够有效提高SG液位控制参数的整定效率以及控制系统稳定性。     

基于结构奇异值综合的蒸汽发生器水位鲁棒控制器设计

针对U型管蒸汽发生器的给水阀开度-水位动力学特性随其本身和给水泵运行工况改变而变化的特性,建立了能定量描述上述原因导致的参数摄动和未建模动态的给水阀开度-水位对象的不确定状态空间模型。基于结构奇异值综合方法设计蒸汽发生器水位鲁棒控制器,并通过选择合适的性能加权函数优化控制系统的鲁棒性能。仿真结果表明,所设计控制器可满足蒸汽发生器从零负荷至满负荷及各种给水泵运行工况下水位自动控制的要求,具有较好的控制品质。     

基于卡尔曼滤波器的蒸汽发生器水位辨识和仿真

为了实现对蒸汽发生器(SG)水位的有效控制,从现代控制论中观测器理论着手,提出一种基于卡尔曼滤波器的假水位检测方法。卡尔曼滤波器是对包含噪声的测定值来估计状态量的有效工具,用卡尔曼滤波器构造一个"假水位"观测器,能够较有效地得到假水位的状态变量。应用该模型对几种典型的反应堆运行功率下SG水位动力学特性进行了仿真计算,结果表明卡尔曼滤波器仿真模型正确辨识出由于SG运行中的逆动力学效应而产生的"假水位",利用该模型可以对SG水位动力学特性进行精确的分析。     

基于模糊控制的核电蒸汽发生器水位的串级自抗扰控制

针对核电站蒸汽发生器所存在的非线性,时变性,大时滞等特点,本文提出了基于模糊控制的蒸汽发生器水位的串级自抗扰控制方案。该方案采用双闭环控制,内环采用带前馈的一阶线性自抗扰控制调节阀,并分别前馈补偿蒸汽扰动和给水扰动,外环采用二阶模糊自抗扰,设计了新型的幂次控制率。仿真结果表明,该控制方案对蒸汽发生器水位具有良好的控制效果,与串级ADRC-PID控制系统相比,不仅具有优良的鲁棒性和抗干扰能力,而且具有可行性。     

Application of a self-organizing fuzzy logic controller to nuclear steam generator level control

In this paper, the self-organizing fuzzy logic controller is investigated for the water level control of a steam generator. In comparison with conventional fuzzy logic controllers, this controller performs the control task with no initial control rules; instead, it creates control rules and tunes input membership functions based on the performance criteria as the control behavior develops, and also modifies its control structure when uncertain disturbance is suspected. Selected tuning parameters of the self-organizing fuzzy logic controller are updated on-line in the learning algorithm, by a gradient descent method. This control algorithm is applied to the water level control of a steam generator model developed by Irving et al. The computer simulation results confirm the good performance of this control algorithm for all power ranges. This control algorithm can be expected to be used for the automatic control of a feedwater control system in a nuclear power plant with digital instrumentation and control systems.     

Life prediction of steam generator tubing due to stress corrosion crack using Monte Carlo Simulation

The failure of steam generator tubing is one of the main accidents that seriously affects the availability and safety of a nuclear power plant. In order to estimate the probability of the failure, a probabilistic model was established to predict the whole life-span and residual life of steam generator (SG) tubing. The failure investigated was stress corrosion cracking (SCC) after the generation of one through-wall axial crack. Two failure modes called rupture mode and leak mode based on probabilistic fracture mechanics were considered in this proposed model. It took into account the variance in tube geometry and material properties, and the variance in residual stresses and operating conditions, all of which govern the propagations of cracks. The proposed model was numerically calculated by using Monte Carlo Simulation (MCS). The plugging criteria were first verified and then the whole life-span and residual life of the SG tubing were obtained. Finally, important sensitivity analysis was also carried out to identify the most important parameters affecting the life of SG tubing. The results will be useful in developing optimum strategies for life-cycle management of the feedwater system in nuclear power plants.     

基于LMIs的核电站蒸汽发生器水位控制策略研究

核电站蒸汽发生器水位常因多种干扰而具有不确定性,因此传统线性水位控制系统较难满足核电站运行要求。针对具有一定不确定性的核电站蒸汽发生器水位模型,根据其特性,借助线性矩阵不等式(LMIs)设计状态反馈H^∞控制器、基于极点配置的H^∞控制器以及H^∞跟踪控制器。在不同稳定工作点下通过仿真试验对上述控制器的效果进行验证和比较,得出了不同稳定工作点下控制策略的特性。     

蒸汽发生器水位改进分数阶控制器研究

蒸汽发生器在瞬态扰动时存在严重的虚假水位现象,增加了低功率水位控制的难度。为研究蒸汽发生器低功率水位控制问题,利用线性参数变化理论,建立了时变的多胞线性参数变化模型。在此模型基础上,提出了分数阶控制器。依据分数阶微积分理论,设计了串级分数阶PI^λD^μ控制器。根据Oustaloup间接离散化方法实现了分数阶PI^λD^μ控制并对Oustaloup方法进行了改进。研究了在负荷变化时,内环和外环4个阶次参数以及改进算法后2个参数变化对系统控制性能的影响。在不同功率区间,相同负荷变化的情况下,对改进后的串级分数阶PI^λD^μ控制器进行了仿真实验。结果表明,所设计的改进串级分数阶PI^λD^μ控制器能有效抑制干扰,分数阶微积分算子的阶次以及改进的Oustaloup方法引入的系数对控制效果均有一定影响,合理调节参数能明显改善系统的控制性能。     

基于GMDH建模的蒸汽发生器水位重构

蒸汽发生器水位指示仪表出现虚假指示或丧失指示的情况时有发生,而目前又没有很好的方法实现蒸汽发生器水位的重新标定,主要靠经验来进行判断,所以当事故或故障发生时严重影响操纵员对核动力装置运行情况的判断。自组织理论模型（GMDH）是建立复杂非线性大系统数学模型十分灵活而通用的方法,在处理复杂非线性对象中能得到很好的效果。本文以主蒸汽管道破口事故下重构蒸汽发生器水位为例,提出了用GMDH重构蒸汽发生器水位的方法,并与仿真结果进行对比。结果表明,GMDH对蒸汽发生器水位重构的相对误差小、精度高,满足实际需要,能为船用核动力装置的安全运行做出指导。     

基于DSP的蒸汽发生器水位模糊控制系统研究

为克服传统的核动力蒸汽发生器水位PID控制器存在的缺点,利用模糊推理技术和数字信号处理器（DSP）技术设计了基于DSP的核动力蒸汽发生器水位模糊控制系统。通过总结熟练操作人员的经验,给出了模糊控制规则,确定了一些重要的控制参数。考虑到控制的实时性,系统的稳定性,采用DSP设计了水位模糊控制系统。仿真实验表明,该系统性能良好。     

蒸汽发生器水位双PI控制的改进研究

蒸汽发生器（SG）水位的控制问题是压水堆核电站紧急停堆的1个重要原因,尤其在低功率情况下,缩胀效应致使水位控制较难。为了避开水位变化初期的假水位的影响,在控制过程中加入判别器来决定水位信号是否参与控制。采用遗传算法对控制器参数进行整定,采用的SG水位模型是简化的数学模型。对控制器中有无判别器的控制效果进行了对比。对比结果表明：加入判别器后,缩短了调节时间,降低了超调量。     

压水堆蒸汽发生器水位的分层自适应模糊控制

针对压水堆蒸汽发生器的水位控制提出了一种分层自适应模糊控制方案。该方案中，2个模糊控制器分层连接，每个模糊控制器均采用典型模糊控制单元，使得模糊规则个数和可调参数个数大大减少，便于在线学习和实时控制。文章分别给出了分层模糊控制器的解析表达式及可调参数的在线学习方法。在压水堆快速加负荷和突然甩负荷的仿真实验中，该方案与PID控制相比，响应快，超调量小，振荡小。     

CPR1000型核电站给水泵事故瞬态分析

以CPR1000型核电站3×50%电动给水泵为研究对象,采用基于RELAP5和Simulink程序开发的CPR1000数字化仪控系统仿真试验台,详细计算分析了给水泵单泵故障和双重故障对反应堆运行的影响及相应的缓解措施。结果表明,给水泵单泵故障对反应堆运行的影响较小,各相关参数能够很快重回事故前的稳态工况。在给水泵双重故障情况下：初始核功率在75%FP及以下时,不会出现蒸汽发生器(SG)低-低水位;初始核功率高于75%FP、汽机初始负荷在90%FP及以下时,需将汽机负荷阶跃降至50%FP,才不会出现SG低-低水位;汽机初始负荷在90%FP以上时,建议停堆。     

核动力装置多变量模糊预测控制仿真研究

为了进一步提高核动力装置的动态控制性能,本文在核动力装置汽轮机和直流蒸汽发生器数学模型的基础上,将基于模糊模型的多变量非线性广义预测控制算法应用于核动力装置主要参数的控制中,包括控制结构和控制器设计。仿真结果显示,当核动力装置负荷的工况变化时,多变量模糊预测控制律下汽轮机相对转速和蒸汽发生器出口压力变化响应时间较经典PID控制律下的快,而PID控制律下的相对转速较多变量模糊预测控制律下的多出3%～5%的超调。由此表明,所采用的多变量模糊预测控制算法能较好地控制核动力装置主要参数的输出,可获得较好的控制效果。     

蒸汽发生器二回路两相流模拟实验装置

由计算机控制的模拟实验台架,是根据压水堆核电站(主要针对秦山核电站)蒸汽发生器的热工参数设计的模拟蒸汽发生器二回路侧热工参数试验的实验台.它可以作为试验平台,用于蒸汽发生器缓蚀剂的动态试验和金属材料的腐蚀考验,促进各种新型缓蚀剂和金属材料在蒸汽发生器中的应用研究的开展.     

水面核电厂蒸汽发生器水位测量技术研究

由于水面核电厂长期在倾斜摇摆状态下运行,导致蒸汽发生器水位测量无法直接采用陆上核电厂成熟的差压式液位测量技术。本文结合差压式液位测量原理,在理论计算分析的基础上提出一种适用于水面核电厂的蒸汽发生器水位测量改进方案,并通过倾斜摇摆台架进行了试验验证。验证结果表明,该改进测量方案能够在水面核电厂倾斜摇摆环境下,快速跟踪各种工况下蒸汽发生器水位的变化,测量稳定可靠。