Control system design for a pressure-tube-type supercritical water-cooled nuclear reactor via a higher order sliding mode method

Nuclear power plants exhibit non-linear and time-variable dynamics.Therefore,designing a control system that sets the reactor power and forces it to follow the desired load is complicated.A supercritical water reactor(SCWR)is a fourth-generation conceptual reactor.In an SCWR,the non-linear dynamics of the reactor require a controller capable of control-ling the nonlinearities.In this study,a pressure-tube-type SCWR was controlled during reactor power maneuvering with a higher order sliding mode,and the reactor outgoing steam temperature and pressure were controlled simultaneously.In an SCWR,the temperature,pressure,and power must be maintained at a setpoint(desired value)during power maneuvering.Reactor point kinetics equations with three groups of delayed neutrons were used in the simulation.Higher-order and classic sliding mode controllers were separately manufactured to control the plant and were compared with the PI controllers speci-fied in previous studies.The controlled parameters were reactor power,steam temperature,and pressure.Notably,for these parameters,the PI controller had certain instabilities in the presence of disturbances.The classic sliding mode controller had a higher accuracy and stability;however its main drawback was the chattering phenomenon.HOSMC was highly accurate and stable and had a small computational cost.In reality,it followed the desired values without oscillations and chattering.

PCTRAN Westinghouse AP1000 Power Control of Pressurized Water Reactor Using Simulink of MATLAB

This paper introduces the simulation, and controls using Simulink of MATLAB for PCTRAN (Personal Computer Transient Analysis) of the power control system (PWR) type pressurized water reactor of PWR WESTINGHOUSE AP1000. The power controller model produces mathematical model description in nonlinear relation form in Simulink of MATLAB which is an important and popular program used at most universities for education. The power controller is described by a block diagram in this paper and some details introduce to clearly understand the work function. The results of action control compared with the PCTRAN programme in modes of automatic and manual control.

Dynamic simulation analysis of molten salt reactor-coupled air-steam combined cycle power generation system

A nonlinear dynamic simulation model based on coordinated control of speed and flow rate for the molten salt reactor and combined cycle systems is proposed here to ensure the coordination and stability between the molten salt reactor and power system.This model considers the impact of thermal properties of fluid variation on accuracy and has been validated with Simulink.This study reveals the capability of the control system to compensate for anomalous situations and maintain shaft stability in the event of perturbations occurring in high-temperature molten salt tank outlet parameters.Meanwhile,the control system’s impact on the system’s dynamic characteristics under molten salt disturbance is also analyzed.The results reveal that after the disturbance occurs,the controlled system benefits from the action of the control,and the overshoot and disturbance amplitude are positively correlated,while the system power and frequency eventually return to the initial values.This simulation model provides a basis for utilizing molten salt reactors for power generation and maintaining grid stability.

Simulation Analysis of Control System in an Innovative Magnetically-Saturated Controllable Reactor

Controllable saturation reactors are widely used in reactive power compensation. The control system of controllable saturation reactor determines adaption speed, accuracy, and stability. First, an innovative type of controllable saturation reactor is introduced. After that the control system is designed, and a self-tuning algorithm in PID controller is proposed in the paper. The algorithm tunes PID parameters automatically with different error signals caused by varied loads in power system. Then the feasibility of the above algorithm is verified by Simulink module of Matlab software. The results of simulation indicate that the control system can efficiently reduce adaption time and overshoot.

2D multi-model general predictive iterative learning control for semi-batch reactor with multiple reactions

Batch to batch temperature control of a semi-batch chemical reactor with heating/cooling system was discussed in this study. Without extensive modeling investigations, a two-dimensional(2D) general predictive iterative learning control(2D-MGPILC) strategy based on the multi-model with time-varying weights was introduced for optimizing the tracking performance of desired temperature profile. This strategy was modeled based on an iterative learning control(ILC) algorithm for a 2D system and designed in the generalized predictive control(GPC) framework. Firstly, a multi-model structure with time-varying weights was developed to describe the complex operation of a general semi-batch reactor. Secondly, the 2 D-MGPILC algorithm was proposed to optimize simultaneously the dynamic performance along the time and batch axes. Finally, simulation for the controller design of a semi-batch reactor with multiple reactions was involved to demonstrate that the satisfactory performance could be achieved despite of the repetitive or non-repetitive disturbances.

Reaction Selectivity Improvement for Reduction of Nitrobenzene in a Packed-Bed Electrode Reactor under Periodic-Current Control

Rectangular wave current control of the electrochemical reduction of nitrobenzene im-proves the selectivity for p-aminophenol(PAP) compared to direct current(d.c.) control at thesame average current density in a flow-by packed-bed reactor.Optimal increase in PAP selectivitycan be obtained at about a frequency of 50Hz and a duty cycle of 0.2.A mathematical model isset up to incorporate the effects of mass transfer,hydrogen evolution and double layer charging,and is solved using the Duhamel’s superposition principle and the modified Crank-Nicolson methodwith the upwind scheme.The conventional d.c.control cases are also calculated for comparison.Calculations can be applied to predict the reaction results under periodic current and d.c.control,but both display the same trends compared to experimental data.

Quantification and control of restrictive ecological factors in acidogenic de-sulfate bioreactor

As an artificial microbial ecosystem, acidogenic de sulfate bioreactor has high efficiency of sulfate removal. The restrictive ecological factors, including causing ecological factors, such as COD/SO 4 2- ratio and sulfate loading rate (Ns), and following ecological factors, such as pH value, oxidation reduction potential (ORP) and alkalinity (ALK) have significant effect on the ability and stability of acidogenic de sulfate bio reactor. Continuous flow and batch test were carried out to investigate the quantification and control of COD/SO 4 2- ratio, Ns, pH value, ORP and ALK in acidogenic de sulfate bioreactor supplied with molasses wastewater as sole organic carbon source and sodium sulfate as electron donor. It was demonstrated that In order to maintain high sulfate removal rate (SRR) of 80% to 90%, the restrictive factors should meet all the requirement as follows: k COD/ SO 4 2-  ratio≥2.0, Ns≤7.5 kg (m 3·d) -1 ,pH=5.7～6.2,ORP=-320～-420 mV and  ALK= 1 500～2 000 mg/L.

Development of a Novel Feedforward Neural Network Model Based on Controllable Parameters for Predicting Effluent Total Nitrogen

The problem of effluent total nitrogen(TN)at most of the wastewater treatment plants(WWTPs)in China is important for meeting the related water quality standards,even under the condition of high energy consumption.To achieve better prediction and control of effluent TN concentration,an efficient prediction model,based on controllable operation parameters,was constructed in a sequencing batch reactor process.Compared with previous models,this model has two main characteristics:①Superficial gas velocity and anoxic time are controllable operation parameters and are selected as the main input parameters instead of dissolved oxygen to improve the model controllability,and②the model prediction accuracy is improved on the basis of a feedforward neural network(FFNN)with algorithm optimization.The results demonstrated that the FFNN model was efficiently optimized by scaled conjugate gradient,and the performance was excellent compared with other models in terms of the correlation coefficient(R).The optimized FFNN model could provide an accurate prediction of effluent TN based on influent water parameters and key control parameters.This study revealed the possible application of the optimized FFNN model for the efficient removal of pollutants and lower energy consumption at most of the WWTPs.

MHD Stability Analysis and Flow Controls of Liquid Metal Free Surface Film Flows as Fusion Reactor PFCs

Numerical and experimental investigation results on the magnetohydrodynamics（MHD） film flows along flat and curved bottom surfaces are summarized in this study. A simplified modeling has been developed to study the liquid metal MHD film state, which has been validated by the existing experimental results. Numerical results on how the inlet velocity（V）, the chute width（W） and the inlet film thickness（d0） affect the MHD film flow state are obtained. MHD stability analysis results are also provided in this study. The results show that strong magnetic fields make the stable V decrease several times compared to the case with no magnetic field,especially small radial magnetic fields（Bn） will have a significant impact on the MHD film flow state. Based on the above numerical and MHD stability analysis results flow control methods are proposed for flat and curved MHD film flows. For curved film flow we firstly proposed a new multi-layers MHD film flow system with a solid metal mesh to get the stable MHD film flows along the curved bottom surface. Experiments on flat and curved MHD film flows are also carried out and some firstly observed results are achieved.

Improved Generalized Predictive Control Algorithm with Offline and Online Identification and Its Application to Fixed Bed Reactor

An improved generalized predictive control algorithm is presented in this paper by incorporating offline identification into onlie identification.Unlike the existing generalized predictive control algorithms.the proposed approach divides parameters of a predictive model into the time invariant and time-varying ones,which are treated respectively by offline and onlie identification algorithms.Therefore,both the reliability and accuracy of the predictive model are improved,Two simulation examples of control of a fixed bed reactor show that this new algorithm is not only reliable and stable in the case of uncertainties and abnormal distrubances,but also adaptable to slow time varying processes.

Dynamics and Predictive Control of Gas Phase Propylene Polymerization in Fluidized Bed Reactors

A two-phase dynamic model,describing gas phase propylene polymerization in a fluidized bed reactor,was used to explore the dynamic behavior and process control of the polypropylene production rate and reactor temperature.The open loop analysis revealed the nonlinear behavior of the polypropylene fluidized bed reactor,justifying the use of an advanced control algorithm for efficient control of the process variables.In this case,a centralized model predictive control(MPC) technique was implemented to control the polypropylene production rate and reactor temperature by manipulating the catalyst feed rate and cooling water flow rate respectively.The corresponding MPC controller was able to track changes in the setpoint smoothly for the reactor temperature and production rate while the setpoint tracking of the conventional proportional-integral(PI) controller was oscillatory with overshoots and obvious interaction between the reactor temperature and production rate loops.The MPC was able to produce controller moves which not only were well within the specified input constraints for both control variables,but also non-aggressive and sufficiently smooth for practical implementations.Furthermore,the closed loop dynamic simulations indicated that the speed of rejecting the process disturbances for the MPC controller were also acceptable for both controlled variables.

Mathematical Model and Advanced Control for Gas-phase Olefin Polymerization in Fluidized-bed Catalytic Reactors

在这研究，在为煤气阶段的催化石蜡聚合建模的开发用 Ziegler-Natta 催化剂的使流体化床的反应堆(FBR ) 被介绍。在乳剂阶段说明在稳固的粒子和包围气体之间的质量和传热的修改数学模型在这个工作被开发包括地点激活反应。在现在的学习开发的这个模型是随后与著名模型相比，也就是水泡生长，混合得好并且为多孔、非多孔的催化剂的模子常数水泡尺寸模型。我们从模型获得了的结果离经常的水泡尺寸模型很靠近，在反应的开始的混合得好的模型和水泡生长模型但是它的全面行为变化了并且在半工作时间以后与水泡生长模型和经常的水泡尺寸模型相比接近混合得好的模型。神经网络的基于的预兆的控制器被实现控制系统，给可接受的结果并且与常规 PID 控制器相比。

Robust Nonlinear Control of Continuous Stirred Tank Reactors

This paper deals with the temperature tracking control problem of continuous stirred tank reactors (CSTRs) widely used in chemical engineering. Design of robust tracking controller for a class of CSTRs plant with uncertainties is presented using input output feedback linearization techniques. The control scheme has been applied to a first order irreversible exothermic reaction process carried out in a CSTR, and simulation results show that it is effective.

Non-integer Order Control Scheme for Pressurized Water Reactor Core Power

Tracking load changes in a pressurized water reactor(PWR)with the help of an efficient core power control scheme in a nuclear power station is very important.The reason is that it is challenging to maintain a stable core power according to the reference value within an acceptable tolerance for the safety of PWR.To overcome the uncertainties,a non-integer-based fractional order control method is demonstrated to control the core power of PWR.The available dynamic model of the reactor core is used in this analysis.Core power is controlled using a modified state feedback approach with a non-integer integral scheme through two different approximations,CRONE(Commande Robuste d’Ordre Non Entier,meaning Non-integer orderRobust Control)and FOMCON(non-integer order modeling and control).Simulation results are produced using MATLAB■program.Both non-integer results are compared with an integer order PI(Proportional Integral)algorithm to justify the effectiveness of the proposed scheme.Sate-spacemodel Core power control Non-integer control Pressurized water reactor PI controller CRONE FOMCON.

Modeling of Fuel Elements Cycling System in Pebble Bed Reactor Based on Timed Places Control Petri Nets

Pebble bed reactors use cycling scheme of spherical fuel elements relying on fuel elements cycling system (FECS). The structure and control logic of FECS are very complex. Each control link has strict requirements on time and sequence. This increases the difficulties of description and analysis. In this paper, timed places control Petri nets (TPCPN) is applied for the modeling of FECS. On this basis the simulation of two important processes, namely uploading fuel elements into the core for the first time and emptying the core is finished by simulation software Arena. The results show that as TPCPN is able to describe different kinds of logic relationship and has time properties and control properties, it’s very suitable for the modeling and analysis of FECS.

Model-Based Split-Range Algorithm for the Temperature Control of a Batch Reactor

In the manufacturing processes of high value-added products in the pharmaceutical, fine chemical polymer and food industry, insufficient control might produce off-grade products. This can cause significant financial losses, or in the pharmaceutical industry, it can result in an unusable batch. In these industries, batch reactors are commonly used, the control of which is essentially a problem of temperature control. In the industry, an increasing number of heating-cooling systems utilising three different temperature levels can be found, which are advantageous from an economic point of view. However, it makes the control more complicated. This paper presents a split-range designing technique using the model of the controlled system with the aim to design a split-range algorithm more specific to the actual sys- tem. The algorithm described provides high control performance when using it with classical PID-based cascade temperature control of jacketed batch reactors;however, it can be used with or as part of other types of controllers, for ex- ample, model-based temperature controllers. The algorithm can be used in the case of systems where only two as well as where three temperature levels are used for temperature control. Besides the switching between the modes of opera- tion and calculating the value of the manipulated variable, one of the most important functions of the split-range algo- rithm is to keep the sign of the gain of the controlled system unchanged. However, with a more system-specific split-range solution, not only can the sign of the gain be kept unchanged, but the gain can also be constant or less de- pendent on the state of the system. Using this solution, the design of the PID controller becomes simpler and can be implemented in existing systems without serious changes.

Control rod drive for high temperature gas cooled reactor

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小型模块化反应堆控制方法综述

小型模块化核反应堆具有建造周期短、安全性高、运维成本低、适应性强、应用领域广等显著优势,广受世界各国关注,也是我国的战略性需求.发展具有自适应、强鲁棒、高可控和高可信特性的新型控制方法,有效降低甚至消除对控制人员值守的依赖,是小型模块化核反应堆的一个重要发展趋势.智能化、自动化的反应堆控制系统通过高效的控制动作来实时跟踪负荷需求,进而有效提高反应堆的稳定性、可靠性和安全性.本文对小型模块化核反应堆控制方法的研究现状进行了综述.本文首先回顾了基于经典控制理论的传统PID控制方法的原理及其优缺点,然后总结了当前应用于反应堆控制系统的一些高精度、高效率智能控制方法,如模糊控制、神经网络控制、智能优化控制、复合控制方法等的主要特点.最后,针对当前小型模块化反应堆控制系统的应用需求和技术难点,本文对智能控制方法的可能发展方向进行了展望.

直流偏磁下磁控电抗器铁芯矢量电磁振动特性

在交直流共同激励的工作方式下,磁控电抗器(magnetically controlled reactor,MCR)受直流偏磁的影响,其电磁特性及振动特性会发生极大的变化。为了精确模拟材料在直流偏磁下的磁化及振动特性,首先基于电工钢片的矢量磁致伸缩逆模型和磁特性测量曲线,采用速度可控粒子群优化(velocity-controlled particle swarm optimization,VCPSO)算法提取并优化模型参数,对磁控电抗器铁芯电工钢片的磁滞和磁致伸缩特性进行分析,并对比实验和仿真曲线,验证磁化特性仿真的准确性;其次,结合矢量磁致伸缩逆模型与MCR有限元模型,模拟MCR铁芯在不同直流偏磁下的矢量电磁振动特性,并分析MCR铁芯位移波形的谐波分量。最后,搭建MCR振动测试系统,验证模型仿真的准确性。研究结果可为磁控电抗器铁芯振动的相关研究提供参考。