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。     

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。     

A fuzzy controller design for nuclear research reactors using the particle swarm optimization algorithm

In this paper, a closed-loop fuzzy logic controller based on the particle swarm optimization algorithm is proposed for controlling the power level of nuclear research reactors. The principle of the fuzzy logic controller is based on the rules constructed from numerical experiments made by means of a computer code for the core dynamics calculation and from human operator's experience and knowledge. In addition to these intuitive and experimental design efforts, consequent parts of the fuzzy rules are optimally (or near optimally) determined using the particle swarm optimization algorithm. The contribution of the proposed algorithm to a reactor control system is investigated in details. The performance of the controller is also tested with numerical simulations in numerous operating conditions from various initial power levels to desired power levels, as well as under disturbance. It is shown that the proposed control system performs satisfactorily under almost all operating conditions, even in the case of very small initial power levels.     

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.     

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。     

Fuzzy Logic Control Application for BWR Recirculation Flow Control System

There has been increasing necessity for load following and/or AFC (Automatic Frequency Control) operation along with the growth in the share of nuclear power generation in the electric power network. Fuzzy logic control was investigated for application to a BWR recirculation flow control system, in order to obtain a rapid generator power response within an allowable neutron flux overshoot. The proposed controller has two control loops, generator power and neutron flux loop. The fuzzy logic is utilized for weighing these control loops and for controlling the neutron flux. By evaluating the controller performance by numerical simulations on the step response for generator power demand with the model BWR recirculation flow system, more rapid response was obtained than that for conventional proportional plus integral controllers with no neutron flux overshoot beyond alarm activation level.     

Adaptive estimator-based dynamic sliding mode control for the water level of nuclear steam generators

Steam Generator (SG) is a crucial component of nuclear power plant. The proper water level control of a nuclear steam generator is of great importance in order to secure the sufficient cooling source of the nuclear reactor and to prevent damage of turbine blades. The water level control problem of steam generators has been a main cause of unexpected shutdowns of nuclear power plants which must be considered for plant safety and availability. The control problem is challenging, especially at low power levels due to shrink and swell phenomena and flow measurement errors. Moreover, the dynamics of steam generator vary as the power level changes. Therefore, it is necessary to improve the water level control system of SG. In this paper, an adaptive estimator-based dynamic sliding mode control method is developed for the level control problem. The proposed method exhibits the desired dynamic properties during the entire output tracking process independent of perturbations. Simulation results are presented to demonstrate the effectiveness of the proposed controller in terms of performance, robustness and stability. Simulation results confirm the improvement in transient response obtained by using the proposed controller.     

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。     

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.     

Design of stability-guaranteed neurofuzzy logic controller for nuclear steam generators

A neurofuzzy logic controller (NFLC), which is implemented by using a multilayer neural network with special types of fuzzifier, inference engine and defuzzifier, is applied to the water level control of a nuclear steam generator (SG). This type of NFLC has the structural advantage that arbitrary two-input, single-output linear controllers can be adequately mapped into a set of specific control rules of the NFLC. In order to design a stability-guaranteed NFLC, the stable sector of the given linear gain is obtained from Lyapunov's stability criteria. Then this sector is mapped into two linear rule tables that are used as the limits of NFLC control rules. The automatic generation of NFLC rule tables is accomplished by using the back-error-propagation (BEP) algorithm. There are two separate paths for the error back propagation in the SG. One considers the level dynamics depending on the tank capacity and the other takes into account the reverse dynamics of the SG. The amounts of error back propagated through these paths show opposite effects in the BEP algorithm from each other for the swell-shrink phenomenon. Through computer simulation it is found that the BEP algorithm adequately generates NFLC rule tables according to given learning parameters.     

Auto-tuned PID controller using a model predictive control methodfor the steam generator water level

In this paper, proportional-integral-derivative (PID) control gains are automatically tuned by using a model predictive control (MPC) method. The MPC has received much attention as a powerful tool for the control of industrial process systems. An MPC-based PID controller can be derived from the second-order linear model of a process. The steam generator is usually described by the well-known fourth-order linear model, which consists of the mass capacity, reverse dynamics, and mechanical oscillation terms. However the important terms in this linear model are the mass capacity and reverse dynamics terms, both of which can be described by a second-order linear system. The proposed auto-tuned PID controller was applied to a linear model of steam generators. The parameters of a linear model for steam generators are very different according to the power levels. The PID gains of the proposed controller are tuned automatically. Also, the proposed controller showed fast water level tracking and small shrink and swell performance by changing only the input-weighting factor according to the power level for the water-level deviation and sudden steam flow disturbances supposed to investigate the tracking performance and swell and shrink characteristics     

P controller with partial feed forward compensation and decoupling control for the steam generator water level

In this paper, a P controller with partial feed forward compensation and decoupling control for the steam generator water level is presented. While taking the steam flowrate as a disturbance to water level, the controller design can be completed in three stages. (1) Main circuit controller is designed without regard to disturbance. Since the transfer function of the steam generator model contains integrate element and differential element, the proportional (P) controller can selected as main circuit controller instead of PID controller for steam generator water level. (2) Partial feed forward compensation is introduced to remove the disturbance from the steam flowrate. If disregarding the differential element, the partial feed forward compensation's designing turns to be very simple. Partial feed forward compensation coefficient is set as reciprocal of P controller gain. (3) The coupling effects between the water level regulating and steam flowrate disturbance can be decreased by model reference decoupling control. The proposed methodology shows satisfactory transient responses, disturbance rejection and robustness.     

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。     

基于模糊神经网络的核动力装置设备故障诊断系统研究

将模糊逻辑与神经网络相结合,对模糊逻辑和神经网络的区别和联系进行了阐述,并探讨了它们之间的结合．模糊神经网络结构及其实现算法,并将这一理论应用于核动力装置故障诊断,建立了基于模糊神经网络的船用核动力装置故障诊断系统。为了验证该系统的有效性,以蒸汽发生器U形管破裂事故为例,进行了仿真实验研究。诊断结果表明该理论方法对此事故完全可以正确识别。     

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。     

基于CFNN的核蒸汽发生器水位控制

鉴于常规的PID控制存在控制对象参数变化时控制参数无法改变的不足,从而根据一个核蒸汽发生器(NSG)的简化数学模型,将一种补偿模糊神经网络(CFNN)用于NSG水位的控制。该网络由于引入了补偿神经元,使网络的容错性更好,系统更稳定。同时在神经网络学习算法中动态优化补偿模糊运算,使网络更适应,训练速度更快。仿真表明,该方法在装置负荷变化时比常规的PID控制方法超调量小,收敛速度快。该网络能在线调整参数,动态优化模糊规则,适于在线学习控制。该控制方法对NSG水位智能控制研究具有一定意义。     

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。     

压水堆负荷跟踪的模糊控制系统

模糊控制理论的发展促进了模糊控制器在压水堆负荷跟踪中的应用。用模糊逻辑控制器和常规ＰＩＤ（比例－积分－微分）控制器相结合，并以输出增闪随功率调整的策略，解决了反应堆负荷跟踪问题，本方法解决了时变非线性对象的闭环控制并克服了基于模型的控制方法的不足，仿真结果显示本文提出的方案不但具有优良的动态特性，而且具有很高的稳态精度，使负荷跟踪控制的自动化程度大为提高。