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.     

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 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.     

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。     

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.     

A steam generator model identification and robust H∞ controller design with ν-gap metric for a feedwater control system

A robust H_∞ controller for the feedwater system of KSNP (Korean Standard Nuclear Power Plant) vertical U-tube type steam generators (UTSG) is presented herein. As the first step of the controller development, a precise thermal–hydraulic model for the steam generator is built. A series of model experiments are performed using the developed thermal–hydraulic model in order to acquire the input–output data sets which represent steam generator characteristics. These data sets are utilized to build simplified steam generator models for control through a system identification algorithm, Simple Process Models. Among the developed steam generator models, the representative models for the designated power ranges are selected by a criterion of ν-gap metric. The representative robust controllers for the selected models are designed utilizing the loop-shaping H_∞ design technique. Finally, the robustness and performance of the proposed controllers are validated and compared against those of PI (proportional–integral) controller. The validation results demonstrated that the proposed H_∞ robust controller has a superior robustness and an enhanced control performance.     

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     

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。     

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。     

核动力装置非线性模型预测协调控制仿真研究

为了进一步提高核动力装置的动态控制性能,本文在阐述核动力装置汽轮机和直流蒸汽发生器的数学模型的基础上,提出将非线性模型预测协调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,多变量非线性预测控制律下汽轮机相对转速和蒸汽发生器出口压力的变化能较快地稳定下来....     

A theoretical model for the calculation of large transients in nuclear natural-circulation U-tube steam generators (Digital code UTSG)

A newly developed nonlinear transient model for the calculation of the dynamic behaviour of a vertical natural-circulation U-tube steam generator together with its steam removal system is presented. The steam generator is considered to consist of a heat exchange section, a top plenum, a downcomer region and a steam removal system with a sequence of relief and/or safety valves, isolation, bypass, turbine-trip and turbine-control valves and a steam turbine. Possible perturbations from outside can be: inlet water temperature, inlet water mass flow and system pressure on the primary side, feed water temperature, feed water mass flow and outlet steam mass flow disturbed by actions of the different valves within the steam removal system on the secondary side. Based on this theoretical model the digital code UTSG has been established. Post-calculations of start-up tests at a PWR nuclear power plant simulating perturbations both on the primary and secondary side of the steam generator and similar calculations for the corresponding ATWS-cases will show the efficiency of the code UTSG and the underlying theoretical model.     

自然循环条件下倒U型管蒸汽发生器一次侧倒流现象关键影响因素研究

倒U型管蒸汽发生器（UTSG）在自然循环条件下存在倒流现象，影响一回路冷却剂系统载热能力及自然循环能力。本文参照芬兰压水堆热工实验装置（PWR PACTEL）中UTSG设计参数，利用计算流体力学（CFD）软件Fluent模拟流量匀速下降工况下UTSG中的倒流现象，研究一次侧运行参数、UTSG设计参数以及二次侧运行参数对于倒流现象的影响。结果表明，提高UTSG一次侧温度、一次侧运行压力、倒U型管热导率将增大UTSG的临界质量流量，使得UTSG更易发生倒流；提高UTSG二次侧给水量、二次侧温度以及倒U型管内壁粗糙度将使得UTSG临界质量流量下降，抑制倒流现象发生；而倒U型管壁厚对倒流现象几乎无影响；相较于改变二回路温度，改变一回路温度对于倒流现象的影响更为显著。本研究结果可为UTSG的参数优化提供一定参考。      

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.     

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.     

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。     

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.     

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。     

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。     

高温气冷堆核蒸汽供应系统出口蒸汽温度的T-S模糊控制方法

高温气冷堆（HTGR）是国际核能界公认的一种具有良好安全特性的堆型,具有第四代核能系统的技术特征,其核蒸汽供应系统（NSSS）复杂的非线性特性,对控制策略的设计提出了挑战。另一方面,T-S模糊控制方法在复杂非线性系统的控制方面存在巨大优势,因此在高温气冷堆核蒸汽供应系统中应用T-S模糊控制方法,可能会获得较传统线性控制方法更好的控制性能。本文提出了一种T-S模糊控制器的系统化设计方法,首先建立高温气冷堆核蒸汽供应系统出口蒸汽温度的T-S模糊控制系统模型;然后基于李雅普诺夫方法,得到T-S模糊控制系统的双线性矩阵不等式（BMI）形式的全局渐近稳定条件;最后通过局部最小化算法求解双线性矩阵不等式,得到T-S模糊控制器的参数。仿真结果表明,按照这一系统化方法设计的T-S模糊控制器较传统的线性PI控制器表现出更好的控制特性。     

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.