High-Speed Trains Automatic Operation with Protection Constraints: A Resilient Nonlinear Gain-based Feedback Control Approach

This paper addresses the control design for automatic train operation of high-speed trains with protection constraints.A new resilient nonlinear gain-based feedback control approach is proposed,which is capable of guaranteeing,under some proper non-restrictive initial conditions,the protection constraints control raised by the distance-to-go(moving authority)curve and automatic train protection in practice.A new hyperbolic tangent function-based model is presented to mimic the whole operation process of high-speed trains.The proposed feedback control methods are easily implementable and computationally inexpensive because the presence of only two feedback gains guarantee satisfactory tracking performance and closed-loop stability,no adaptations of unknown parameters,function approximation of unknown nonlinearities,and attenuation of external disturbances in the proposed control strategies.Finally,rigorous proofs and comparative simulation results are given to demonstrate the effectiveness of the proposed approaches.

CMOS Automatic Gain Control Circuit with DC Offset Cancellation for FM/cw Ladar

This paper presented an automatic gain control(AGC) circuit suitable for FM/cw ladar. The proposed architecture was based on two-stage variable gain amplifier(VGA) chain with a novel DC offset canceller circuit, which contained an improved Gilbert cell and a Gm-C feedback loop. To keep the VGA with a linearity in dB characteristic, an improved exponential gain control circuit was introduced. The AGC was implemented in 0.18 μm standard CMOS process. Simulation and measurement results verified that its gain ranged from-20 dB to 30 dB, and bandwidth ranged from 100 kHz to 10 MHz. Its power consumption was 19.8 mW under a voltage supply of 3.3 V.

A Novel Cascaded PID Controller for Automatic Generation Control Analysis With Renewable Sources

Present day power scenarios demand a high quality uninterrupted power supply and needs environmental issues to be addressed. Both concerns can be dealt with by the introduction of the renewable sources to the existing power system. Thus, automatic generation control(AGC) with diverse renewable sources and a modified-cascaded controller are presented in the paper.Also, a new hybrid scheme of the improved teaching learning based optimization-differential evolution(hITLBO-DE) algorithm is applied for providing optimization of controller parameters. A study of the system with a technique such as TLBO applied to a proportional integral derivative(PID), integral double derivative(IDD) and PIDD is compared to hITLBO-DE tuned cascaded controller with dynamic load change.The suggested methodology has been extensively applied to a 2-area system with a diverse source power system with various operation time non-linearities such as dead-band of, generation rate constraint and reheat thermal units. The multi-area system with reheat thermal plants, hydel plants and a unit of a wind-diesel combination is tested with the cascaded controller scheme with a different controller setting for each area. The variation of the load is taken within 1% to 5% of the connected load and robustness analysis is shown by modifying essential factors simultaneously by± 30%. Finally, the proposed scheme of controller and optimization technique is also tested with a 5-equal area thermal system with non-linearities. The simulation results demonstrate the superiority of the proposed controller and algorithm under a dynamically changing load.

Design of a Proportional-Integral-Derivative Controller for an Automatic Generation Control of Multi-area Power Thermal Systems Using Firefly Algorithm

Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system operation and control,automatic generation control(AGC) plays a crucial role. In this paper, multi-area(Five areas: area 1, area 2, area 3, area 4 and area 5) reheat thermal power systems are considered with proportional-integral-derivative(PID) controller as a supplementary controller. Each area in the investigated power system is equipped with appropriate governor unit, turbine with reheater unit, generator and speed regulator unit. The PID controller parameters are optimized by considering nature bio-inspired firefly algorithm(FFA). The experimental results demonstrated the comparison of the proposed system performance(FFA-PID)with optimized PID controller based genetic algorithm(GAPID) and particle swarm optimization(PSO) technique(PSOPID) for the same investigated power system. The results proved the efficiency of employing the integral time absolute error(ITAE) cost function with one percent step load perturbation(1 % SLP) in area 1. The proposed system based FFA achieved the least settling time compared to using the GA or the PSO algorithms, while, it attained good results with respect to the peak overshoot/undershoot. In addition, the FFA performance is improved with the increased number of iterations which outperformed the other optimization algorithms based controller.

MAS Based Distributed Automatic Generation Control for Cyber-Physical Microgrid System

The microgrid is a typical cyber-physical microgrid system(CPMS). The physical unconventional distributed generators(DGs) are intermittent and inverter-interfaced which makes them very different to control. The cyber components,such as the embedded computer and communication network,are equipped with DGs, to process and transmit the necessary information for the controllers. In order to ensure system-wide observability, controllability and stabilization for the microgrid,the cyber and physical component need to be integrated. For the physical component of CPMS, the droop-control method is popular as it can be applied in both modes of operation to improve the grid transient performance. Traditional droop control methods have the drawback of the inherent trade-off between power sharing and voltage and frequency regulation. In this paper, the global information(such as the average voltage and the output active power of the microgrid and so on) are acquired distributedly based on multi-agent system(MAS). Based on the global information from cyber components of CPMS, automatic generation control(AGC) and automatic voltage control(AVC)are proposed to deal with the drawback of traditional droop control. Simulation studies in PSCAD demonstrate the effectiveness of the proposed control methods.

Cluster DetectionMethod of Endogenous Security Abnormal Attack Behavior in Air Traffic Control Network

In order to enhance the accuracy of Air Traffic Control(ATC)cybersecurity attack detection,in this paper,a new clustering detection method is designed for air traffic control network security attacks.The feature set for ATC cybersecurity attacks is constructed by setting the feature states,adding recursive features,and determining the feature criticality.The expected information gain and entropy of the feature data are computed to determine the information gain of the feature data and reduce the interference of similar feature data.An autoencoder is introduced into the AI(artificial intelligence)algorithm to encode and decode the characteristics of ATC network security attack behavior to reduce the dimensionality of the ATC network security attack behavior data.Based on the above processing,an unsupervised learning algorithm for clustering detection of ATC network security attacks is designed.First,determine the distance between the clustering clusters of ATC network security attack behavior characteristics,calculate the clustering threshold,and construct the initial clustering center.Then,the new average value of all feature objects in each cluster is recalculated as the new cluster center.Second,it traverses all objects in a cluster of ATC network security attack behavior feature data.Finally,the cluster detection of ATC network security attack behavior is completed by the computation of objective functions.The experiment took three groups of experimental attack behavior data sets as the test object,and took the detection rate,false detection rate and recall rate as the test indicators,and selected three similar methods for comparative test.The experimental results show that the detection rate of this method is about 98%,the false positive rate is below 1%,and the recall rate is above 97%.Research shows that this method can improve the detection performance of security attacks in air traffic control network.

新能源电力系统AGC调频容量监测设计

文章提出了用于新能源电力系统自动发电控制(Automatic Generation Control,AGC)的实时调频容量评估方法,以满足控制区的自动发电控制调频能力分析需求。根据AGC调频容量考核标准,整理了影响调频容量的主要因素,并运用历史数据预测调频标准差。以贵州黔源电力镇宁某水电站和光伏站作为例,评估AGC调频容量。实验结果证实,应用所提方法能有效地分配调频容量。

Improved Smith prediction monitoring AGC system based on feedback-assisted iterative learning control

The performance of Smith prediction monitoring automatic gauge control(AGC) system is influenced by model mismatching greatly in strip rolling process. Aiming at this problem, a feedback-assisted iterative learning control strategy, which learned unknown modeling error by using previous control information repeatedly, was introduced into Smith prediction monitoring AGC system. Firstly, conventional Smith predictor and improved Smith predictor with PI-P controller were analyzed. Secondly, on the basis of establishing of feedback-assisted iterative learning control strategy for improved Smith predictor, process control signal update law and control error were deduced, then convergence condition of this strategy was put forward and proved. Finally, after modeling the automatic position control system, the PI-P Smith prediction monitoring AGC system with feedback-assisted iterative learning control was researched through simulation. Simulation results indicate that this system remains stable during model mismatching. The robustness and response of monitoring AGC is improved by development of feedback-assisted iterative learning control strategy for PI-P Smith predictor.

一种用于毫米波探测系统的变步长LMS-AGC方案

在毫米波探测系统中,自动增益控制(AGC)是信号处理系统的关键技术之一,其作用是应对大动态范围的中频信号接收。本文阐述了一种数字自动增益控制(DAGC)的实现方案,通过对中频信号的数字采样进行处理,采用基于平均功率参量的变步长LMS-AGC自适应算法,将自适应滤波器的变步长思想应用到AGC方案中,并对其步长算法进行优化。通过对比普通功率检测自动增益控制和固定步长LMS-AGC方案,本文提出的变步长LMS-AGC方案具有更快的收敛速度和更小的稳态误差。

精轧AGC系统仿真实验教学平台设计与开发

在新工科背景下为了培养学生实践创新能力,设计开发了以钢铁企业热连轧精轧自动厚度控制系统(Automatic Gauge Control, AGC)为对象的虚拟仿真实验教学平台。该实验教学平台从本科自动化专业多门实践类课程的教学需求出发,依次设计了精轧系统轧制规程仿真模块和AGC控制系统仿真模块,并细化为6个具体的实验项目,较好地模拟了多机架带钢热连轧精轧的生产控制过程。实践表明,该实验教学平台有效地提升了学生工程实践能力和综合创新能力,为高校新工科卓越人才培养提供了良好的支撑。

机载激光测深系统强度数据AGC补偿异常区域识别及改正

机载激光测深系统(Airborne Laser Bathymetry,ALB)因集成了具有独特水体穿透能力的绿波段(532nm)而被广泛用于水深测量。除地形数据外,ALB还记录了地物目标的辐射特性(后向散射强度),可用于条带配准、海底底质分类和几何建模。然而,由于自动增益控制(Automatic Gain Control,AGC)设计局限,增益值调整存在延缓,对于裸露岩石、水域等高返回、低返回目标较多的海岛海岸带区域,强度补偿异常问题格外突出。针对该问题本文设计了一种基于双向移动的局部加权强度改正方法,提出索引共享机制辅以地形信息实现有效强度数据精确提取;以扫描周期为依据进行扫描线分割,通过柯尔莫可洛夫-斯米洛夫检验进行强度补偿异常区识别;通过对邻近扫描线和邻域强度联合加权进行强度改正,保证强度细节的同时较好地消除与邻域强度偏差,独特的双向移动策略能有效削弱改正不足积累造成的强度改正精度下降问题。实验证明该方法能有效解决AGC补偿异常问题,相较于改正前,改正后的强度数据平均绝对百分比误差降低了约0.27,均方根误差下降了约693,异常区强度与邻域强度偏差控制在26DN(Digital Number)以内,得到高质量强度图像。

基于AGC线性化的谐振式加速度计相位噪声分析

谐振式加速度计系统运行过程中会引入噪声,导致输出信号的相位发生偏移,从而影响测频精度。同时,由于自动增益控制(AGC)回路非线性的影响,噪声的传递无法直接利用传递函数分析。为了减小噪声的影响,根据谐振式加速度计的工作原理与噪声理论,对谐振回路中引入的各种噪声进行了传递路径的线性化分析与数学推导,给出了相位噪声表达式。MATLAB曲线,Simulink噪声模型与谐振式加速度计高速采样的相位噪声一致,验证了相位噪声表达式与噪声模型的正确性。

基于AGC调频分区控制的光储联合系统参与市场投标策略

为充分发挥光储联合系统提供调频辅助服务的能力、提高联合系统的收益,提出了一种基于自动发电控制(automaticgenerationcontrol,AGC)调频分区控制的光储联合系统参与市场的投标策略。首先,考虑了光储系统运行特性和电网频率波动不确定性,提出了光储系统参与能量-调频市场的日前-实时两阶段交易方法。其次,提出了光储系统参与AGC的实时调频控制方法,根据区域控制偏差所处控制域动态分配光储系统所承担的调节量。然后,构建了光储联合系统参与电力市场的多时间尺度投标优化模型,其中日前市场考虑了潜在的实时能量偏差,实时市场利用滚动优化方法反馈校正多种不确定因素。最后,通过算例分析验证了该策略在充分考虑电力系统频率安全稳定的前提下,使利润增加了14.9%,显著提高了光储联合系统的收益。

基于反相积分峰值检测法的高频信号AGC系统

针对现有非射频自动增益控制系统难以处理高频信号的问题,提出了一种反相积分峰值检测方法,并基于此方法设计了高频信号自动增益控制系统。反相积分峰值检测法是针对低频MCU设计的高频信号峰值检测方法,可以实现宽频带上的高精度峰值检测。系统由反相积分峰值检测模块对输出信号进行峰值检测,由MCU控制模块根据峰值检测结果调控可变增益放大模块的增益,实现自动增益控制。实验结果表明:该自动增益控制系统最高工作带宽可达200 MHz,相对误差在0.7%以内,相较现有基于非射频峰值检测法的自动增益控制系统,最高工作带宽在控制精度更高的前提下提升到2倍以上。

区域新能源电力系统AGC调频容量实时评估方法

针对高比例可再生能源接入下电力系统惯量水平持续降低、弱频率调节能力会危及电网安全运行等问题,提出一种区域新能源电力系统自动发电控制AGC(automatic generation control)调频容量实时评估方法,以确定控制区的AGC调频能力分析需求。首先,依据AGC调频容量考核标准,梳理调频容量的主要影响因素,并获取调频容量、调频标准差与调频表现间的联系。其次,综合应用传统机组、负荷、新能源、联络线历史数据,基于极限学习机ELM(extreme learning machine)模型预测调频标准差,利用调频表现达标概率分布确定区域电力系统的调频容量。最后,以河北某电网为例进行AGC调频容量的评估,验证了所提方法AGC调频容量更小,调频表现更优,具有更好的安全性和经济性。

一种大动态范围数字 AGC快速控制算法

在大动态范围的复杂通信系统中,自动增益控制系统的性能起着至关重要的作用。针对传统自动增益控制系统的动态范围较小及收敛速度较慢的问题,提出了一种大动态范围数字AGC快速控制算法。该算法采用射频峰值检测以及大信号指示的方式实现对射频功率的快速检测;采用平均功率的方式对中频信号功率进行滑动平均,准确获取中频信号的平均功率;结合中频和射频增益控制策略,对接收信道的增益进行分配以及快速控制,使得射频信号经过射频单元后始终位于模数转换器(Analog to Digital Converter,ADC)的动态范围内,从而实现射频信号的稳定接收。仿真结果表明,相较于传统算法,所提算法的收敛时间由毫秒级提高到了微秒级,动态范围大幅提升。

Research on Wind Farm Participation in Power Grid AGC Control

Since wind power has the features of being intermittent and unpredictable, and usually needs transmission over long distances, grid integration of large-scale wind power will exert signif icant influence on power grid planning and construction, and will make a heavy impact on the safe and reliable operation of power systems. To deal with the diff iculties of large scale wind power dispatch, this paper presents a new automatic generation control (AGC) scheme that involves the participation of wind farms. The scheme is based on ultra-short-term wind power forecast. The author establishes a generation output distribution optimization mode for the power system with wind farms and verif ies the feasibility of the scheme by an example.

大庆永跃光伏电站AGC系统设计与实现

本文介绍了永跃光伏电站自动发电控制(AGC)系统的设计与实现,介绍了AGC的约束条件和分配策略,以及AGC的实现和AGC程序模块化的通用性,为清洁能源电站有功自动控制提供理论依据。

拉西瓦700MW大型水轮机组自动发电控制(AGC)调节性能提升分析

在碳达峰碳中和目标以及风光大基地规划建设的新形势下,西北电网新能源电量渗透率升至45%时,西北电网面临严峻的稳态频率调节挑战,需巨型水轮机组自动发电控制(AGC)调节控制西北电网稳态频率,其有功调节的响应时间与调节速率对于系统稳态频率控制具有重要的意义。通过研究拉西瓦700 MW大型水轮机组自动发电控制(AGC)调节各环节之间的相互关系,分析了调节过程中那个环节未及时响应,并针对未能及时响应的环节进行了分析和优化,最终可提升自动发电控制(AGC)的调节响应时间和调节速率。

机组AGC及深度调峰控制性能优化

江苏徐矿综合利用发电有限公司2台300 MW亚临界燃煤发电机组,自2010年投产以来经历多次检修,机组主辅机性能产生变化,且由于机组增加对外供热,原设计控制方式无法协调锅炉能量—汽机需求—电气功率三者的平衡,加剧了AGC、一次调频调节品质的恶化,且无法适应当前电网深调工况需求。通过对机组自动控制系统进行相应逻辑优化、参数调整,在保证各主辅机安全运行的前提下,有效提高机组“两个细则”性能指标,同时实现30%~100%深度调峰下机组稳定经济运行。