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。     

基于T-S型模糊神经网络的反应堆功率调节研究

压水堆核动力装置通过对反应堆功率的控制,实现大范围工况变化下对负荷的跟踪,并维持反应堆主要参数的稳定。为了提高核功率的控制效果,提出一种基于T-S型模糊神经网络的自适应模糊控制器,并通过多种工况仿真试验下与经典比例-积分(PI)控制器比较,说明了该控制器的优越性。     

压水堆核电厂负荷跟踪系统设计与特性研究

压水堆核电厂通过功率控制系统调节反应堆的反应性,以达到负荷跟踪的目的。本文设计的功率控制系统利用模糊控制器对棒速和硼浓度的联合控制做出最优选择,并利用功率补偿通道加快响应速度。MATLAB(Matrix Laboratory)的仿真结果证明该系统具有优良的负荷跟踪特性。利用电力系统分析综合程序(PSASP)的自定义模型功能,将该控制系统模块接入核电厂全系统模型,仿真结果表明压水堆核电厂的负荷跟踪能力可达到行业技术标准,并能满足电网的日负荷调峰要求。     

采用典型模糊控制器实现压水堆稳压器的综合控制

对压水堆稳压器的压力和水位控制．提出了一种模糊综合控制方案。采用3个典型模糊控制器分别对电加热器、喷淋卸压阀和上充阀进行控制;在稳压器压力典型模糊控制器中采用了积分分离方法。本文对汽轮机负荷阶跃变化、线性变化、甩负荷3种工况进行了控制系统的仿真实验。结果表明,稳压器的压力以及水位的瞬态和稳态控制性能都得到了较大改善,明显优于GA-FC和PID控制方案。     

液态熔盐堆堆芯功率模糊PID控制

液态熔盐堆采用熔融氟化盐为燃料,燃料熔盐出口温度是衡量熔盐堆安全的重要指标。通过堆芯功率控制可实现燃料熔盐出口温度控制。将液态熔盐堆堆芯划分成内区和外区,并基于能量守恒原理建立堆芯非线性模型,采用微扰理论对非线性模型进行线性化。基于堆芯线性化模型,采用模糊比例-积分-微分（PID）控制器设计堆芯功率控制系统。以熔盐增殖堆（MSBR）为例,开展堆芯功率控制仿真。结果表明,引入10-3、2×10-3阶跃反应性时,模糊PID控制器可以减小系统响应的上冲幅度和超调量,并且在堆芯功率发生了较大的负荷变化时,模糊PID控制器可以对堆芯功率的变化实现良好跟踪。故所采用的模糊PID控制器具有良好的动态性能,可实现对堆芯功率的良好控制。      

压水堆负荷跟踪模型预测控制器设计

通过对压水堆微分方程数学模型进行Taylor级数展开,建立了压水堆的状态空间模型,设计了一种模型预测控制器,以实现负荷跟踪的自动控制。将二次规划(QP)用于求取模型预测控制系统的最优解。通过模拟实验评估所设计的基于二次规划的模型预测控制器QPMPC的负荷跟踪性能,模拟结果表明:所设计的QPMPC控制器能够快速、有效地跟踪压水堆负荷变化。     

压水堆负荷跟踪运行的新模式

综述了压水堆负荷跟踪运行的控制方式，并指出了其优缺点，对压水堆负荷跟踪运行的新模式－ＭｏｄｅＫ的控制棒分组在堆芯中的分布，以及控制棒提棒过程进行了分析，认为其基本控制原理正是大系统控制理论中化整为零，分别对待思想的具体应用，从而提高了自动化程度。     

小型模块化反应堆冷却剂平均温度的预测控制方法

小堆的应用相对大型压水堆更具有灵活性，需要考虑在并网和孤岛运行下的负荷变动需求，然而棒速控制下的冷却剂平均温度被控系统是非自衡系统，且具有较强的刚性、开环不稳定性以及复杂的非线性。本文设计了一种改进型动态矩阵控制器（DMC）。该控制器拓宽了传统预测控制的适用范围，克服了该算法的适用局限性。通过与程序单元控制以及比例积分（PI）控制进行对比，验证了改进型DMC预测控制下的冷却剂平均温度系统稳态误差更小，响应速度更快，具有更好的跟踪性能。      

核反应堆功率模糊广义预测控制

为了满足核电机组提高负荷跟随性能的需求,基于T-S模糊模型,设计了针对点堆中子动力学方程的模糊广义预测控制器。利用并行分布补偿(PDC)方法,将基于线性化方程的各局部预测控制器在强非线性的全局范围内统一起来,从而扩大了反应堆功率控制中广义预测控制器的适用范围。计算机仿真结果表明,对于三种典型的反应堆运行工况,所设计的控制器都能在保证安全的前提下,在全局范围内表现出良好的负荷跟随能力。     

模糊鲁棒控制方法在核反应堆功率控制中的应用

为了对核反应堆功率进行实时控制,以适应电网负荷的变化需求,基于T-S模糊模型设计了核反应堆功率模糊鲁棒控制器。首先使用状态反馈设计了局部控制器,然后应用并行补偿方法设计全局控制器。线性矩阵不等式的求解证明所设计的控制器是稳定的。仿真结果表明,对于3种典型工况变化,所设计的控制器对反应堆的功率变化能进行很好的控制。     

Application of Fuzzy Logic Controller to Load-Follow Operations in Pressurized Water Reactors

The fuzzy logic controller was developed to control load-follow operations in pressurized water reactors. The reactor core characteristics change according to different fuel cycles or core exposures, thus making a nonlinear time-varying control problem. This proposed method, however, does not require a mathematical model to design the controller, and so avoids redesigning or tuning controller gain for various cores. Clearly, this method is very suitable for reactor load-following operation control. The control system has two subsystems: one is to track the desired power, and the other is to keep axial offset close to the target value. Both controllers use fuzzy logic: one is the conventional type, and the other uses fuzzy logic to tune the parameters of the controller so the controller can correspond to various core characteristics. Simulation results show that the control system performs well for different cores, and so this system is useful for load-follow operation.     

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.     

Application of fuzzy logic control system for regulation of differential pressure in Liquid Zone Control System

In this paper, fuzzy control scheme has been proposed for generating regulating signals to feed and bleed control valves, which are used in Liquid Zone Control System (LZCS) for maintaining constant pressure difference between gas outlet header and delay tank. The LZCS and the existing PI controller are briefly described. It is followed by the design of Fuzzy Controller. It consists of seven symmetric triangular input membership functions and output membership functions each. Mamdani implication has been used to infer output contribution from each rule. The centroid type of defuzzification method is employed to get the crisp output values. The fuzzy logic controller for feed and bleed control valves so designed has been validated by performing a variety of experiments on a full scale LZCS test setup at Bhabha Atomic Research Centre and its performance is analyzed and compared to that obtained with existing PI controller. In comparison with the existing PI controller, the fuzzy logic controller’s performance is superior in all cases considered.     

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.     

强流束晕-混沌的模糊逻辑控制研究

以周期性磁场聚焦传输通道中的K-V(Kapchinskij-Vladimirskij)分布离子束为例,引入带偏置的升余弦函数近似刻画实际磁场,理论分析了通道中强流离子束的束晕-混沌动力学行为。针对束晕-混沌的控制问题,提出了束晕-混沌的模糊逻辑控制方法。模糊控制器采用Mamdani推理系统,其输出作为控制因子线性调整外部磁场强度。用模糊相平面法分析了控制系统的稳定性。仿真结果显示：在控制条件下,混沌变化的束包络半径被稳定控制;将该方法应用于多粒子模型,消除了束晕及其再生现象,束的品质获得较大提高。该模糊控制方法具有不依赖束输运数学模型、控制器简单、磁场调节呈线性关系、易于工程实现等优点。     

Design of an intelligent fuzzy logic controller for a nuclear research reactor

The main objective of this paper is to design an intelligent controller system based on the concepts of fuzzy logic. This latter will be used to control the power of a nuclear reactor. The principle of this controller is based on rules established from experiments used with a classical controller and from the knowledge and the expertise of the operators of the reactor. This intelligent controller could be used in parallel with the actual system, which is semiautomatic, as a decision aided system to assist the operators in the control room.     

Design and optimization of fuzzy-PID controller for the nuclear reactor power control

This paper introduces a fuzzy proportional-integral-derivative (fuzzy-PID) control strategy, and applies it to the nuclear reactor power control system. At the fuzzy-PID control strategy, the fuzzy logic controller (FLC) is exploited to extend the finite sets of PID gains to the possible combinations of PID gains in stable region and the genetic algorithm to improve the ‘extending’ precision through quadratic optimization for the membership function (MF) of the FLC. Thus the FLC tunes the gains of PID controller to adapt the model changing with the power. The fuzzy-PID has been designed and simulated to control the reactor power. The simulation results show the favorable performance of the fuzzy-PID controller.     

A neural network controller for load following operation of nuclear reactors

Nuclear reactors are in nature nonlinear and their parameters vary with time as a function of power level, fuel burnup, and control rod worth. Therefore, these characteristics must be considered if large power variations occur in power plant working regimes (for example in load following conditions). In this paper a neural network controller (NNC) is presented. A robust optimal self-tuning regulator (ROSTR) response is used as a reference trajectory to determine the feedback, feedforward and observer gains of the NNC. The NNC displayed good stability and performance for a wide range of operation as well as considerable reduction in computation time in regard to ROSTR and fuzzy logic controller (FAROC).     

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.     

Comparison between a continuous and a discrete method for the aggregation and deffuzification stages of a TRIGA reactor power fuzzy controller

This paper presents a comparison of the performance of two different methods to realize the aggregation and the centre of gravity stages of a fuzzy controller that is under development for its integration, as an alternative power control algorithm, in the control console of the TRIGA Mark III reactor of the Mexican Nuclear Centre. In one case, an innovative method determines, in every control cycle, the group of lines that define the fuzzy aggregated set of the rule base in the continuous domain of the output variable. Likewise, the centre of gravity of this aggregated set is analytically obtained, and the corresponding controller is named exact or continuous. In the other case, a method is used to determine, in one step, both the aggregated set and its centre of gravity using the classical discretization of the universe of discourse of the output variable, thus leading to the discrete fuzzy controller. These methods were simulated in the ascent and regulation of neutron power in a TRIGA Mark III reactor. The performance parameters used for the comparison between the two methods were: The required number of floating point operations, the time required to attain a certain power level, the neutron power time response, and the reactor period values.