Reduced-order method for nuclear reactor primary circuit calculation

Accurate real-time simulations of nuclear reactor circuit systems are particularly important for system safety analysis and design.To effectively improve computational efficiency without reducing accuracy,this study establishes a thermal-hydraulics reduced-order model(ROM)for nuclear reactor circuit systems.The full-order circuit system calculation model is first established and verified and then used to calculate the thermal-hydraulic properties of the circuit system under different states as snapshots.The proper orthogonal decomposition method is used to extract the basis functions from snapshots,and the ROM is constructed using the least-squares method,effectively reducing the difficulty in constructing the ROM.A comparison between the full-order simulation and ROM prediction results of the AP1000 circuit system shows that the proposed ROM can improve computational efficiency by 1500 times while achieving a maximum relative error of 0.223%.This research develops a new direction and perspective for the digital twin modeling of nuclear reactor system circuits.

Reduced-Order Observer-Based LQR Controller Design for Rotary Inverted Pendulum

The Rotary Inverted Pendulum(RIP)is a widely used underactuated mechanical system in various applications such as bipedal robots and skyscraper stabilization where attitude control presents a significant challenge.Despite the implementation of various control strategies to maintain equilibrium,optimally tuning control gains to effectively mitigate uncertain nonlinearities in system dynamics remains elusive.Existing methods frequently rely on extensive experimental data or the designer’s expertise,presenting a notable drawback.This paper proposes a novel tracking control approach for RIP,utilizing a Linear Quadratic Regulator(LQR)in combination with a reduced-order observer.Initially,the RIP system is mathematically modeled using the Newton-Euler-Lagrange method.Subsequently,a composite controller is devised that integrates an LQR for generating nominal control signals and a reduced-order observer for reconstructing unmeasured states.This approach enhances the controller’s robustness by eliminating differential terms from the observer,thereby attenuating unknown disturbances.Thorough numerical simulations and experimental evaluations demonstrate the system’s capability to maintain balance below50Hz and achieve precise tracking below1.4 rad,validating the effectiveness of the proposed control scheme.

A Reduced-Order Modeling of Multi-Port RC Networks by Means of Graph Partitioning

A modified reduced-order method for RC networks which takes a division-and-conquest strategy is presented.The whole network is partitioned into a set of sub-networks at first,then each of them is reduced by Krylov subspace techniques,and finally all the reduced sub-networks are incorporated together.With some accuracy,this method can reduce the number of both nodes and components of the circuit comparing to the traditional methods which usually only offer a reduced net with less nodes.This can markedly accelerate the sparse-matrix-based simulators whose performance is dominated by the entity of the matrix or the number of components of the circuits.

血清NY-ESO-1自身抗体和MMP1联合检测对食管鳞状细胞癌的诊断价值

目的:探讨血清基质金属蛋白酶-1(matrix metalloproteinase-1,MMP1)和纽约食管鳞状细胞癌抗原-1(New York esophageal squamous cell carcinoma 1,NY-ESO-1)自身抗体联合检测在食管鳞状细胞癌中的诊断意义。方法:应用酶联免疫吸附实验检测120例食管鳞状细胞癌患者和120例正常对照血清中MMP1和NY-ESO-1自身抗体的表达水平,采用受试者工作特征(receiver operating characteristic,ROC)曲线评价诊断效能。结果:血清MMP1和NY-ESO-1自身抗体在食管鳞状细胞癌患者中的表达均明显高于正常对照[(8.070±5.738)ng/mL vs(4.331±3.137)ng/mL,Z=6.214,P<0.001;0.463±0.571 vs 0.156±0.086,Z=5.210,P<0.001]。ROC曲线显示,当血清MMP1为最佳诊断临界值10.586 ng/mL时,其在诊断食管鳞状细胞癌的曲线下面积(area under the ROC curve,AUC)为0.732(95%CI:0.671~0.787),敏感度为24.2%,特异度为95.0%。NY-ESO-1自身抗体诊断食管鳞状细胞癌AUC为0.695(95%CI:0.632~0.752),敏感度为33.0%,特异度为95.0%。MMP1和NY-ESO-1自身抗体联合检测诊断食管鳞状细胞癌的AUC为0.800(95%CI:0.744~0.849),敏感度为47.5%,特异度为95.0%。结论:血清MMP1和NY-ESO-1自身抗体联合检测可能有助于提高食管鳞状细胞癌的诊断效能。

Observer based projective reduced-order synchronization of different chaotic systems

The projective reduced-order synchronization of two different chaotic systems with different orders is investigated based on the observer design in this paper.According to the observer theory,the reduced-order observer is designed.The projective synchronization can be realized by choosing the transition matrix of the observer as a diagonal matrix.Further,the synchronization between hyperchaotic Chen system(fourth order)and Rssler system(third order)is taken as the example to demonstrate the effectiveness of the proposed observer.Numerical simulations confirm the effectiveness of the method.

Reduced-Order Observer-Based Leader-Following Formation Control for Discrete-Time Linear Multi-Agent Systems

Formation control of discrete-time linear multi-agent systems using directed switching topology is considered in this work via a reduced-order observer, in which a formation control protocol is proposed under the assumption that each directed communication topology has a directed spanning tree. By utilizing the relative outputs of neighboring agents, a reduced-order observer is designed for each following agent. A multi-step control algorithm is established based on the Lyapunov method and the modified discrete-time algebraic Riccati equation. A sufficient condition is given to ensure that the discrete-time linear multi-agent system can achieve the expected leader-following formation.Finally, numerical examples are provided so as to demonstrate the effectiveness of the obtained results.

A reduced-order extrapolation algorithm based on CNLSMFE formulation and POD technique for two-dimensional Sobolev equations

A reduced-order extrapolation algorithm based on Crank-Nicolson least-squares mixed finite element （CNLSMFE） formulation and proper orthogonal decomposition （POD） technique for two-dimensional （2D） Sobolev equations is established. The error estimates of the reduced-order CNLSMFE solutions and the implementation for the reduced-order extrapolation algorithm are provided. A numerical example is used to show that the results of numerical computations are consistent with theoretical conclusions. Moreover, it is shown that the reduced-order extrapolation algorithm is feasible and efficient for seeking numerical solutions to 2D Sobolev equations.

Reduced-Order GPIO Based Dynamic Event-Triggered Tracking Control of a Networked One-DOF Link Manipulator Without Velocity Measurement

In networked robot manipulators that deeply integrate control, communication and computation, the controller design needs to take into consideration the limited or costly system resources and the presence of disturbances/uncertainties. To cope with these requirements, this paper proposes a novel dynamic event-triggered robust tracking control method for a onedegree of freedom(DOF) link manipulator with external disturbance and system uncertainties via a reduced-order generalized proportional-integral observer(GPIO). By only using the sampled-data position signal, a new sampled-data robust output feedback tracking controller is proposed based on a reduced-order GPIO to attenuate the undesirable influence of the external disturbance and the system uncertainties. To save the communication resources, we propose a discrete-time dynamic event-triggering mechanism(DETM), where the estimates and the control signal are transmitted and computed only when the proposed discrete-time DETM is violated. It is shown that with the proposed control method, both tracking control properties and communication properties can be significantly improved. Finally, simulation results are shown to demonstrate the feasibility and efficacy of the proposed control approach.

Reduced-order Kalman filtering for state constrained linear systems

This paper aims at solving the state filtering problem for linear systems with state constraints. Three classes of typical state constraints, i.e., linear equality, quadratic equality and inequality, are discussed. By using the linear relationships among different state variables, a reduced-order Kalman filter is derived for the system with linear equality constraints. Afterwards, such a solution is applied to the cases of the quadratic equality constraint and inequality constraints and the two constrained state filtering problems are transformed into two relative constrained optimization problems. Then they are solved by the Lagrangian multiplier and linear matrix inequality techniques, respectively. Finally, two simple tracking examples are provided to illustrate the effectiveness of the reduced-order filters.

Generalized reduced-order synchronization of chaotic system based on fast slide mode

A new kind of generalized reduced-order synchronization of different chaotic systems is proposed in this paper. It is shown that dynamical evolution of third-order oscillator can be synchronized with the canonical projection of a fourth-order chaotic system generated through nonsingular states transformation from a cell neural net chaotic system. In this sense, it is said that generalized synchronization is achieved in reduced-order. The synchronization discussed here expands the scope of reduced-order synchronization studied in relevant literatures. In this way, we can achieve generalized reduced-order synchronization between many famous chaotic systems such as the second-order Drifting system and the third-order Lorenz system by designing a fast slide mode controller. Simulation results are provided to verify the operation of the designed synchronization.

Reduced-order finite element method based on POD for fractional Tricomi-type equation

The reduced-order finite element method （FEM） based on a proper orthogo- nal decomposition （POD） theory is applied to the time fractional Tricomi-type equation. The present method is an improvement on the general FEM. It can significantly save mem- ory space and effectively relieve the computing load due to its reconstruction of POD basis functions. Furthermore, the reduced-order finite element （FE） scheme is shown to be un- conditionally stable, and error estimation is derived in detail. Two numerical examples are presented to show the feasibility and effectiveness of the method for time fractional differential equations （FDEs）.

Computationally efficient direction finding using polynomial rooting with reduced-order and real-valued computations

The root multiple signal classification（root-MUSIC） algorithm is one of the most important techniques for direction of arrival（DOA） estimation. Using a uniform linear array（ULA） composed of M sensors, this method usually estimates L signal DOAs by finding roots that lie closest to the unit circle of a（2M-1）-order polynomial, where L 〈 M. A novel efficient root-MUSIC-based method for direction estimation is presented, in which the order of polynomial is efficiently reduced to 2L. Compared with the unitary root-MUSIC（U-root-MUSIC） approach which involves real-valued computations only in the subspace decomposition stage, both tasks of subspace decomposition and polynomial rooting are implemented with real-valued computations in the new technique,which hence shows a significant efficiency advantage over most state-of-the-art techniques. Numerical simulations are conducted to verify the correctness and efficiency of the new estimator.

IGBT Temperature Field Monitoring Based on Reduced-order Model

With the rapid development of the world economy,IGBT has been widely used in motor drive and electric energy conversion.In order to timely detect the fatigue damage of IGBT,it is necessary to monitor the junction temperature of IGBT.In order to realize the fast calculation of IGBT junction temperature,a finite element method of IGBT temperature field reduction is proposed in this paper.Firstly,the finite element calculation process of IGBT temperature field is introduced and the linear equations of finite element calculation of temperature field are derived.Temperature field data of different working conditions are obtained by finite element simulation to form the sample space.Then the covariance matrix of the sample space is constructed,whose proper orthogonal decomposition and modal extraction are carried out.Reasonable basis vector space is selected to complete the low dimensional expression of temperature vector inside and outside the sample space.Finally,the reduced-order model of temperature field finite element is obtained and solved.The results of the reduced order model are compared with those of the finite element method,and the performance of the reduced-order model is evaluated from two aspects of accuracy and rapidity.

Nonlinear Control of an Induction Motor Using a Reduced-Order Extended Sliding Mode Observer for Rotor Flux and Speed Sensorless Estimation

This article proposes an innovative strategy to the problem of non-linear estimation of states for electrical machine systems. This method allows the estimation of variables that are difficult to access or that are simply impossible to measure. Thus, as compared with a full-order sliding mode observer, in order to reduce the execution time of the estimation, a reduced-order discrete-time Extended sliding mode observer is proposed for on-line estimation of rotor flux, speed and rotor resistance in an induction motor using a robust feedback linearization control. Simulations results on Matlab-Simulink environment for a 1.8 kW induction motor are presented to prove the effectiveness and high robustness of the proposed nonlinear control and observer against modeling uncertainty and measurement noise.

基于ESO的仿蝙蝠扑翼飞行器姿态控制仿真

针对仿蝙蝠扑翼飞行器的纵向气动特性不稳定、易受扰动的问题,设计了一种基于扩张状态观测器(ESO)的姿态控制方法,实现了扑翼飞行器姿态的稳定与抗干扰控制。首先建立仿蝙蝠扑翼飞行器的动力学模型;进而在该模型基础上分析了扑翼飞行器的纵向稳定性;然后将系统的不确定部分与各种未知的外界扰动作为系统的总扰动,引入ESO模块对总扰动进行实时观测与跟踪;最后在原有的PID控制器中加入扰动补偿环节。数值仿真结果表明,基于ESO的控制算法对于仿蝙蝠扑翼飞行器的控制效果显著优于基于PID的控制方法,阶跃响应的调节时间加快41.27%,对系统输入的白噪声干扰波动峰值从6.02%降低到2.82%,正弦扰动的波动峰值从11.56%降低到3.22%。

基于ESO的分拣并联机器人无标定视觉伺服自适应滑模控制

针对无标定分拣并联机器人需获取精确图像雅可比矩阵的问题,同时为克服图像检测误差、建模误差及外部干扰对无标定视觉伺服系统的影响,提出一种基于扩张状态观测器(extended state observer,ESO)的分拣并联机器人无标定视觉伺服自适应滑模控制方法。通过将表征机器人图像空间与任务空间映射关系的图像雅可比矩阵与系统不确定项集总到同一通道的状态方程,引入ESO对分拣并联机器人视觉伺服系统的集总不确定性进行在线估计,设计一种基于扩张状态观测器的自适应积分滑模控制器,并通过设计自适应律动态调整滑模控制切换增益,以提高视觉伺服系统精度,同时达到抑制滑模控制抖振的效果。采用Lyapunov稳定性理论证明该控制方法的稳定性,最后通过仿真实验验证了所提出视觉伺服自适应滑模控制方法的可行性和有效性。

Research of influence of reduced-order boundary on accuracy and solution of interior points

The flow field with a high order scheme is usually calculated so as to solve complex flow problems and describe the flow structure accurately. However, there are two problems, i.e., the reduced-order boundary is inevitable and the order of the scheme at the discontinuous shock wave contained in the flow field as the supersonic flow field is low. It is questionable whether the reduced-order boundary and the low-order scheme at the shock wave have an effect on the numerical solution and accuracy of the flow field inside. In this paper, according to the actual situation of the direct numerical simulation of the flow field, two model equations with the exact solutions are solved, which are steady and unsteady, respectively, to study the question with a high order scheme at the interior of the domain and the reduced-order method at the boundary and center of the domain. Comparing with the exact solutions, it is found that the effect of reduced-order exists and cannot be ignored. In addition, the other two model equations with the exact solutions, which are often used in fluid mechanics, are also studied with the same process for the reduced-order problem.

Reduced-order proper orthogonal decomposition extrapolating finite volume element format for two-dimensional hyperbolic equations

This paper is concerned with establishing a reduced-order extrapolating fi- nite volume element （FVE） format based on proper orthogonal decomposition （POD） for two-dimensional （2D） hyperbolic equations. For this purpose, a semi discrete variational format relative time and a fully discrete FVE format for the 2D hyperbolic equations are built, and a set of snapshots from the very few FVE solutions are extracted on the first very short time interval. Then, the POD basis from the snapshots is formulated, and the reduced-order POD extrapolating FVE format containing very few degrees of freedom but holding sufficiently high accuracy is built. Next, the error estimates of the reduced-order solutions and the algorithm procedure for solving the reduced-order for- mat are furnished. Finally, a numerical example is shown to confirm the correctness of theoretical conclusions. This means that the format is efficient and feasible to solve the 2D hyperbolic equations.

基于FxTSMC-ESO的永磁同步电机调速系统滑模控制

针对永磁同步电机速度环中存在的外部负载扰动问题,为了提高速度环控制系统的动态性和鲁棒性,提出一种基于新型固定时间滑模控制器与扩张状态观测器的控制方法。所提出的滑模控制器简化了收敛时间公式,解决了快速响应与抑制抖振的矛盾。为了进一步提升调速系统的鲁棒性,采用固定时间收敛的扩张状态观测器对控制器的扰动进行前馈补偿,该观测器不仅可以减小趋近律的开关函数增益,还能实现扰动的精准观测。仿真验证了所提滑模控制方法的有效性。

基于ESO的双馈风力发电机模型预测直接功率控制

针对双馈风力发电机(DFIG)运行过程中因电机参数摄动以及电网电压突变等不确定因素对控制系统的影响,提出一种扩张状态观测器(ESO)与模型预测直接功率控制(MPDPC)相结合的控制策略。首先分析了传统MPDPC中存在的系统耦合项、模型误差及外部扰动等对控制系统的影响,为了减小此影响,应用ESO进行相关参数估计。在此基础上,结合模型预测控制理论建立了功率预测数学模型。在不同工况下进行了仿真实验并和传统MPDPC进行比较,结果表明所提控制策略具有较强的鲁棒性和抗干扰能力。