基于变论域模糊PID的液态熔盐堆堆芯功率控制

液态熔盐堆堆芯系统具有非线性、时变性等特点,模糊比例积分微分(PID)控制技术因初始论域不能跟随误差变化而伸缩,使得系统的控制精度降低,故设计了一种基于变论域模糊PID控制器的堆芯功率控制策略。以熔盐增殖堆MSBR堆芯为例,在堆芯入口温度扰动或堆芯反应性扰动下,使用Matlab/Simulink对PID控制、模糊PID控制与变论域模糊PID控制下的效果进行仿真对比。结果表明,基于变论域模糊PID控制器建立的堆芯功率控制系统响应速度更快,超调量更小,控制效果更佳。     

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。     

核反应堆堆芯功率模糊切换控制系统开发及应用

为利用不同类型控制器的性能优势,基于堆芯模糊多模型,利用比例-积分-微分(PID)控制器和模糊控制器,结合T-S型模糊规则设计模糊切换控制器。以三里岛核电站压水堆堆型堆芯为例,建立一套堆芯功率模糊切换控制系统并开展仿真研究。结果表明,与传统PID控制器相比,所设计的堆芯模糊切换控制器更适用于堆芯反应性阶跃扰动和堆芯冷却剂进口温度阶跃扰动下的堆芯功率控制。     

T-S型模糊切换控制器在堆芯功率控制中的应用

采用传统比例-积分-微分(PID)控制器开展堆芯功率控制,控制过程中存在超调量大、调节时间长的问题。为解决这一问题,基于堆芯传递函数模型,采用T-S型模糊规则对比例-微分(PD)控制器、PID控制器、模糊控制器进行加权及切换,设计T-S型模糊切换控制器。以铅冷快堆堆芯功率控制为例,建立堆芯功率T-S型模糊切换控制系统,开展堆芯相对功率设定值阶跃、堆芯冷却剂进口温度扰动仿真。结果表明,基于堆芯传递函数模型设计的T-S型模糊切换控制器可以实现对堆芯功率的良好控制。     

T-S型模糊切换控制器在堆芯功率控制中的应用#br# #br#

The traditional PID controller is used to control the core power, which has the problems of large overshoot and long regulating time in the control process. In order to solve this problem, based on the core transfer function model, the PD controller, the PID controller and the fuzzy controller are weighted and switched by T-S fuzzy rules, and T-S fuzzy switching controller is designed. Taking the core power control of a lead cooled fast reactor as an example, a T-S fuzzy switching control system of the core power is established to simulate the relative power setpoint value step and the core inlet coolant temperature disturbance. The results show that the T-S fuzzy switching controller designed based on the core transfer function model can achieve a good control of the core power.     

Sugeno型二维模糊控制器设计及其优化研究

基于MATLAB/Simulink平台设计了某研究堆功率调节系统各环节模型,并设计了应用于该研究堆功率调节系统中的Sugeno型二维模糊控制器。仿真分析结果表明,Sugeno型二维模糊控制器可应用于该研究堆功率调节系统,且在超调量、调节时间等方面的性能优于经典PID控制器。本文提出了一种优化方法,优化后的模糊控制器性能得到改善,且性能（超调量、调节时间、振荡性能等方面）优于经典PID控制器。该优化方法是一种有效的模糊控制器优化方法。     

模糊控制应用于研究堆功率调节系统的研究

基于MATLAB/Simulink平台构建了研究堆功率调节系统闭环内所有环节的数学模型,设计了Mamdani型二维模糊控制器。在Simulink平台环境下,通过仿真分析了系统的稳定性及其控制特性。结果表明,采用该模糊控制器的反应堆功率调节系统是稳定的,并具备良好的跟随特性,其控制性能优于经典的PID控制器。     

基于NSGA-Ⅱ算法的核反应堆功率LQG控制器设计

反应堆功率控制系统的设计与核电厂的安全性和经济性息息相关。为提高其功率控制性能,本研究以某压水堆核电厂为研究对象,建立了其非线性动态数学模型,推导了其状态空间模型;采用线性二次型高斯（LQG）最优控制方法,设计了堆芯功率控制器;进一步基于遗传算法NSGA-Ⅱ对LQR权重系数进行了多目标优化;将本文所设计的控制器与传统PID控制器进行了典型工况的仿真对比。结果表明,与传统PID控制器相比,基于NSGA-Ⅱ方法优化的LQG控制器不但响应快速、控制精度高、稳定性好,而且具有良好的鲁棒性,能获得更优越的堆芯功率控制效果。     

Multivariable Online Adaptive PID Controller for Plasma Current,Shape, and Position in Tokamaks

Nuclear fusion is one of the newest and most promising clean and safe energies hence, it imposes a new research area of control. In this paper, the design of a multivariable adaptive proportional-integral-derivative (PID) controller for the control of the plasma current, shape and position to ensure the safe operation of the fusion reactor is successfully developed. The recursive least square algorithm is used in an alternative way as an adaptation mechanism for tuning PID controller gains. Since stability is a vital issue in the evaluation of control systems, therefore stability analysis of the proposed controller is developed using the Lyapunov stability theory. The main objective of plasma current, shape and position controller in fusion reactors is to improve the stability and the performance of tokamak magnetic systems without contravening the limits imposed by the actuating coils voltages physical limitations. The proposed APID (adaptive PID) controller tunes online its parameters to cope with the presence of the disturbance or any parameters changes occur during the operation. The results of the proposed APID on a simulation code of a tokamak show a noteworthy improvement with respect to those obtained with other control techniques in the cases of changing the initial controller gains, adding disturbance signal and variation in the reactor model parameters.     

核反应堆模糊PID控制的实验模拟系统

在核反应堆实验模拟系统上进行了核反应堆模糊ＰＩＤ控制的研究,研究结果表明：采用模糊ＰＩＤ控制器控制核反应堆系统,在负载改变时能较快抑制冷却剂温度变化,稳态精度高,可以达到很好的控制效果。     

基于模糊多模型的堆芯功率控制

传统的堆芯功率PID控制器是基于单一功率水平处的堆芯局部模型设计的,难以准确描述整个堆芯功率水平范围的控制。因此,本文基于5个不同功率水平下的传递函数模型,通过三角隶属度函数加权,建立堆芯模糊多模型,并依据该模型设计堆芯功率模糊PID控制。以TMI型压水堆堆芯为对象,开展不同初始功率水平下的堆芯功率跟踪、堆芯进口温度扰动的控制仿真。结果表明,基于模糊多模型设计的堆芯功率模糊PID控制器可实现对堆芯功率的良好控制。     

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     

Application of artificial intelligence techniques in modeling and control of a nuclear power plant pressurizer system

In pressurized water reactor (PWR) nuclear power plants (NPPs) pressure control in the primary loops is fundamental for keeping the reactor in a safety condition and improve the generation process efficiency. The main component responsible for this task is the pressurizer. The pressurizer pressure control system (PPCS) utilizes heaters and spray valves to maintain the pressure within an operating band during steady state conditions, and limits the pressure changes during transient conditions. Relief and safety valves provide overpressure protection for the reactor coolant system (RCS) to ensure system integrity. Various protective reactor trips are generated if the system parameters exceed safe bounds. Historically, a proportional-integral-derivative (PID) controller is used in PWRs to keep the pressure in the set point, during those operation conditions. The purpose of this study is two-fold: first, to develop a pressurizer model based on artificial neural networks (ANNs); secondly, to develop fuzzy controllers for the PWR pressurizer modeled by the ANN and compare their performance with conventional ones. Data from a 2785 MWth Westinghouse 3-loop PWR simulator was used to test both the pressurizer ANN model and the fuzzy controllers. The simulation results show that the pressurizer ANN model responses agree reasonably well with those of the simulated power plant pressurizer, and that the fuzzy controllers have better performance compared with conventional ones.     

研究堆Mamdani型模糊控制器设计优化方法

Mamdani型模糊控制器的设计优化尚无系统、成熟的方法。本文针对应用于研究堆功率调节系统的Mamdani型模糊控制器,提出了两种设计优化方法,即非均匀分布输出隶属函数法和细化且非均匀分布隶属函数法,并在MATLAB/Simulink平台下分析了优化后模糊控制器的控制特性。结果表明：优化后模糊控制器的控制性能得到改善,且性能优于经典PID控制器。本文提出的两种设计优化方法是行之有效的Mamdani型模糊控制器优化方法。     

Application of model predictive control strategy based on fuzzy identification to an SP-100 space reactor

In this work, a model predictive control method combined with fuzzy identification, is applied to the design of the thermoelectric (TE) power control in the SP-100 space reactor. The future TE power is predicted by using the fuzzy model identified by a subtractive clustering method of a fast and robust algorithm. The objectives of the proposed fuzzy model predictive controller are to minimize both the difference between the predicted TE power and the desired power, and the variation of control drum angle that adjusts the control reactivity. Also, the objectives are subject to maximum and minimum control drum angle and maximum drum angle variation speed. The genetic algorithm that is effective in accomplishing multiple objectives is used to optimize the fuzzy model predictive controller. A lumped parameter simulation model of the SP-100 nuclear space reactor is used to verify the proposed controller. The results of numerical simulations to check the performance of the proposed controller show that the TE generator power level controlled by the proposed controller could track the target power level effectively, satisfying all control constraints.     

小型铅铋冷却快堆堆芯功率控制研究

铅铋冷却快堆多用于海洋、山区等偏远特殊环境的孤网供电,用户特性要求小型铅铋冷却快堆需具有良好的负荷跟踪能力。本文将3种不同的控制方法应用于铅铋冷却快堆堆芯功率控制,通过引入噪声、死区、时滞等环节对控制器的稳定性和设定值跟踪能力进行了测试。结果表明,比例-积分-微分（PID）控制器很难达到较好的控制效果,因此工业应用时往往加入了其他环节以保证PID控制器的稳定性。自抗扰（ADRC）控制器和H∞鲁棒控制器都具有良好的抗噪能力,能够独立地完成较好的控制效果,但良好的抗噪能力要牺牲一定的灵敏性。通过对3种控制器的比较分析表明,由于仿真计算对实际对象进行了简化,在这样的条件下所设计的控制器应选择较为保守的参数。     

核反应堆神经元PID控制的计算机模拟系统

设计了核反应堆神经元比例积分微分（PID）控制器,对控制过程进行了计算机模型,模拟结果表明,神经元PID控制器能自动调整自身参数到理想状态,并在核反应堆的控制过程中达到好的控制结果。     

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。     

基于流量功率比恒定的小型铅基快堆运行研究

为开展小型铅基快堆运行策略研究,建立堆芯传递函数模型,利用比例-积分-微分（PID）控制器,结合控制棒驱动机构,分别设计堆芯流量功率比恒定与堆芯稳定核功率的运行方案。分别建立不同运行策略下的控制系统,开展一回路流量阶跃和堆芯反应性扰动仿真。结果表明,在引入一回路流量阶跃下降工况下,稳定核功率运行方案由于堆芯功率恒定而导致堆芯出口温度过高;在流量功率比恒定方案下,堆芯功率跟随一回路流量下降从而保证堆芯出口温度迅速稳定在安全范围内;在阶跃反应性扰动下,2种方案均可迅速调控堆芯功率的上冲幅度和超调量,堆芯出口温度基本维持恒定。