Exploring Variability in Sea Level at a Tide Gauge Station through Control Charts

Monitoring temporal changes in sea level is important in assessing coastal risk.Sea level anomalies at a tide gauge station,if kinematically conceived,include systematic variations such as trend,acceleration,periodic oscillations,and random disturbances.Among them,the non-stationary nature of the random sea level variations of known or unknown origin at coastal regions has been long recognized by the sea level community.This study proposes the analyses of subgroups of random residual statistics of a rigorously formulated kinematic model solution of tide gauge variations using X-bar and S control charts.The approach is demonstrated using Key West,Florida tide gauge records.The mean and standard errors of 5-year-long subgroups of the residuals revealed that sea level changes at this location have been progressively intensifying from 1913 to the present.Increasing oscillations in sea level at this locality may be attributed partly to the thermal expansion of seawater with increasing temperatures causing larger buoyancy-related sea level fluctuations as well as the intensification of atmospheric events including wind patterns and the impact of changes in inverted barometer effects that will alter coastal risk assessments for the future.

Analysis of debris flow control effect and hazard assessment in Xinqiao Gully,Wenchuan M_(s)8.0 earthquake area based on numerical simulation

Xinqiao Gully is located in the area of the 2008 Wenchuan M_(s)8.0 earthquake in Sichuan province,China.Based on the investigation of the 2023"6-26"Xinqiao Gully debris flow event,this study assessed the effectiveness of the debris flow control project and evaluated the debris flow hazards.Through field investigation and numerical simulation methods,the indicators of flow intensity reduction rate and storage capacity fullness were proposed to quantify the effectiveness of the engineering measures in the debris flow event.The simulation results show that the debris flow control project reduced the flow intensity by41.05%to 64.61%.The storage capacity of the dam decreases gradually from upstream to the mouth of the gully,thus effectively intercepting and controlling the debris flow.By evaluating the debris flow of different recurrence intervals,further measures are recommended for managing debris flow events.

Integrated Evaluation of Air Traffic Controller Workload Based on Matter-Element Analysis

A model for evaluating the controller workload was presented based on matter-element analysis, particularly from a mansystem engineering perspective. On the basis of a questionnaire survey, 18 kinds of indexes which influence the controller workload were determined. By establishing the classical field and node field of the controller workload, the correlation function of the controller workload grade was obtained; then the correlation degree and estimated grade of controller workload were given. A case study verifies the feasibility of the proposed evaluation method.

基于B/S架构的远程会诊质控系统的设计与应用

目的研发远程会诊质控系统,在区域内实现远程会诊质控、管理、监管、考评、统计和持续改进的信息化。方法2020年,组建多学科团队,运用智力激励法和专题小组讨论法,基于B/S架构研发远程会诊质控系统,与既有远程会诊信息系统完全嵌合兼容,满足远程会诊全流程质量管理的功能需求。结果针对远程会诊质控工作要求,系统设计研发了质控管理、质控考评、实时监管、统计分析4个子模块,可满足远程会诊全流程质量管理的功能需求。结论该质控系统创新了远程会诊信息化质量管理模式,在区域内实现了远程会诊全流程的信息化管理,取得了较好的质量管理成效,有效促进区域内远程会诊工作的推进和发展。

基于STM32的步进电机加减速轨迹规划算法

针对传统步进电机开环控制下加减速过程中柔性冲击大、失步和过冲等问题,结合STM32单片机提出了一种离散化的、带有电流调节的S曲线加减速控制算法。首先,通过多项式算法构建连续光滑的S曲线,根据矩频特性拟合转速和转矩的关系,联立转速和功率的关系,推导出电流计算方法;然后,对连续的S曲线进行等时间间隔采样,完成对S曲线的离散化;最后,在Keil平台进行算法代码编写,将编译后的工程文件下载到STM32中,通过步进电机的速度和位置跟踪实验验证了算法的有效性。

基于Super-Twisting滑模S面的无人机路径跟踪控制

针对小型固定翼无人机在执行任务时跟踪精度低以及容易受外界风影响的问题,设计基于Super-Twisting滑模S面(STSM S-Plane)的路径跟踪控制器,同时采用内外双环控制模式。外环即速度环采用Super-Twisting滑模控制,内环即姿态环采用S面控制。考虑到S面控制求导易导致积分爆炸的问题引入了二阶微分器,并对外界风组成进行建模研究。最后通过空间特殊曲线来验证所设计算法的控制性能。仿真结果表明,所设计的算法可以实现固定翼无人机对期望路径的精确跟踪,并具有良好的鲁棒性和抗干扰性能。

售货机升降系统S型速度控制策略

在传统三闭环控制方式下,售货机升降接货系统易因启停过程中加速度突变产生冲击,导致系统运行不平稳。针对这一问题,文中对传统升降系统加减速控制策略进行改进,加入前馈和微分负反馈,提出一种S型速度曲线控制算法。根据路径规划判别条件将S型速度曲线分为七段式、六段式和四段式3种,并给出各路径约束条件下的参数求解方法和具体执行流程。将该算法运用到升降控制系统中进行仿真和实际工况测试,实验结果表明,与传统三闭环控制相比,文中所提控制策略可以提高售货机升降系统运行的平稳性,减小冲击,使速度曲线更加柔和,并能够保持较好的跟踪性能。

Adaptive fuzzy controller for a class of strict-feedback nonaffine nonlinear systems

A robust adaptive fuzzy control scheme is presented for a class of strict-feedback nonaffine nonlinear systems with modeling uncertainties and external disturbances by using a backstepping approach.Fuzzy logic systems are employed to approximate the unknown parts of the desired virtual controls,and the approximation errors of fuzzy systems are only required to be norm-bounded.The function tanh（·） is introduced to avoid problems associated with sgn（·）.The tracking error is guaranteed to be uniformly ultimately bounded with the aid of an additional adaptive compensation term.Chua＇s circuit system and R o¨ssler system are presented to illustrate the feasibility and effectiveness of the proposed control technique.

Flexible predictive power-split control for battery-supercapacitor systems of electric vehicles using IVHS

The utilization of traffic information received from intelligent vehicle highway systems(IVHS) to plan velocity and split output power for multi-source vehicles is currently a research hotspot. However, it is an open issue to plan vehicle velocity and distribute output power between different supply units simultaneously due to the strongly coupling characteristic of the velocity planning and the power distribution. To address this issue, a flexible predictive power-split control strategy based on IVHS is proposed for electric vehicles(EVs) equipped with battery-supercapacitor system(BSS). Unlike hierarchical strategies to plan vehicle velocity and distribute output power separately, a monolayer model predictive control(MPC) method is employed to optimize them online at the same time. Firstly, a flexible velocity planning strategy is designed based on the signal phase and time(SPAT) information received from IVHS and then the Pontryagin’s minimum principle(PMP) is adopted to formulate the optimal control problem of the BSS. Then, the flexible velocity planning strategy and the optimal control problem of BSS are embedded into an MPC framework, which is online solved using the shooting method in a fashion of receding horizon. Simulation results verify that the proposed strategy achieves a superior performance compared with the hierarchical strategy in terms of transportation efficiency, battery capacity loss, energy consumption and computation time.

固定翼UAV路径跟踪的全局稳定积分滑模S面控制

针对固定翼无人机的三维路径跟踪控制问题,设计了一种基于全局稳定积分滑模S面模型的内外环控制器。控制器外环采用全局稳定积分滑模控制,内环采用S面控制。设计控制器外环的全局稳定积分滑模控制律,并采用Lyapunov理论证明所设计控制律的稳定性。对内环的指令信号设计S面控制器,考虑到S面控制器中求导的复杂性,引入二阶微分器,解决内环中导数存在积分爆炸的问题。半物理仿真试验结果表明,提出的控制器能精确跟踪期望路径,具有良好的控制性能和抗干扰性能。

基于T-S MPC的车辆自适应巡航控制策略研究

针对于汽车自适应巡航系统面对复杂工况时自适应性不强的问题,提出了一种基于T-S模糊变权重模型预测控制(Takagi-Sugeno fuzzy model predictive control,T-S MPC)的自适应巡航分层控制策略。首先上层控制器基于安全距离模型将自适应巡航系统划分为定速巡航模式、多目标优化控制的跟随模式和紧急制动模式;下层控制器基于车辆逆动力学模型,将上层控制器输出的期望加速度转变为节气门开度或制动压力;其次考虑到权重系数对控制精度的影响,建立基于T-S模糊控制的变权重模型预测控制器;最后搭建Carsim Simulink联合仿真平台,验证控制策略的准确性、适应性和跟踪响应速度。结果表明,在定速巡航工况时,T-S MPC控制方法跟踪响应时间为1.54 s,较PID和传统MPC控制跟踪响应快;在跟随和混合工况时,T-S MPC控制方法均方根误差为分别为0.3073、2.775,均低于PID、PID+LQR和传统MPC控制的均方根误差、并且自适应性好,有效提高了跟车性能与安全性。

基于S函数的调节阀粘滞特性检测方法

调节阀粘滞特性引起的振荡是工业控制回路性能恶化的最常见来源。目前虽然已有许多检测调节阀粘滞特性的方法,但这些方法的复杂性或存在的缺陷限制着其在实际工况中的具体应用。本文提出了一种检测过程控制回路中调节阀粘滞故障的新方法。该方法将控制器输出(OP)和过程变量(PV)的变化(ΔPV)在相平面图中所构成变化趋势与标准S函数进行对比,根据实际函数趋势与标准S函数间的差异计算相关系数,通过相关系数的数值具体得出调节阀中是否存在粘滞特性。仿真实例和实际工业数据分析实验验证了提出方法的有效性。

基于自适应S面算法的小型ROV艏向和深度运动控制研究

带缆遥控水下机器人(ROV)系统艏向与深度运动具有强非线性和运行环境不确定性等特点。针对ROV的运动特点,构建运动控制模型并进行化简,通过构建自适应S面控制法对艏向与深度进行控制,并利用Lyapunov的稳定性判据证明该控制法的稳定性,通过仿真验证了该控制法具有良好的稳定性和控制品质。同时,与S面控制法相比,自适应S面控制具有更好的动态性能与静态性能,调节速度快、稳定性强,能够准确控制ROV运动。

Optimization of S-surface controller for autonomous underwater vehicle with immune-genetic algorithm

To deduce error and fussy work of manual adjustment of parameters for an S-surface controller in underwater vehicle motion control, the immune-genetic optimization of S-surface controller of an underwater vehicle was proposed. The ability of producing various antibodies for the immune algorithm, the self-adjustment of antibody density, and the antigen immune memory were used to realize the rapid convergence of S-surface controller parameters. It avoided loitering near the local peak value. Deduction of the S-surface controller was given. General process of the immune-genetic algorithm was described and immune-genetic optimization of S-surface controller parameters was discussed. Definitive results were obtained from many simulation experiments and lake experiments, which indicate that the algorithm can get good effect in optimizing the nonlinear motion controller parameters of an underwater vehicle.

Enhancing Mild Cognitive Impairment Detection through Efficient Magnetic Resonance Image Analysis

Neuroimaging has emerged over the last few decades as a crucial tool in diagnosing Alzheimer’s disease(AD).Mild cognitive impairment(MCI)is a condition that falls between the spectrum of normal cognitive function and AD.However,previous studies have mainly used handcrafted features to classify MCI,AD,and normal control(NC)individuals.This paper focuses on using gray matter(GM)scans obtained through magnetic resonance imaging(MRI)for the diagnosis of individuals with MCI,AD,and NC.To improve classification performance,we developed two transfer learning strategies with data augmentation(i.e.,shear range,rotation,zoom range,channel shift).The first approach is a deep Siamese network(DSN),and the second approach involves using a cross-domain strategy with customized VGG-16.We performed experiments on the Alzheimer’s Disease Neuroimaging Initiative(ADNI)dataset to evaluate the performance of our proposed models.Our experimental results demonstrate superior performance in classifying the three binary classification tasks:NC vs.AD,NC vs.MCI,and MCI vs.AD.Specifically,we achieved a classification accuracy of 97.68%,94.25%,and 92.18%for the three cases,respectively.Our study proposes two transfer learning strategies with data augmentation to accurately diagnose MCI,AD,and normal control individuals using GM scans.Our findings provide promising results for future research and clinical applications in the early detection and diagnosis of AD.

Design of Novel S-plane Controller of Autonomous Underwater Vehicle Established on Sliding Mode Control

Based on the deep analysis of the mathematical model of an autonomous underwater vehicle( AUV),comprehensive considerations are given to the coupling effect of AUV's longitudinal velocity on the other degrees of freedom. In the meantime,discussions are made on the influence of residual buoyancy and restoring moment.A novel S-plane controller established on sliding mode control( SMC) is hereby proposed in this study. The strengths of traditional S-plane controller including simple structure and easily adjustable parameters are maintained in the improved design while the weakness of unsatisfactory control effect at the time of high-speed operation is also overcome. Lyapunov function is introduced to make the stability analysis of the controller before it is successfully applied to the basic motion control of AUV-X. Then the comparative experiment test is carried out between the traditional S-plane controller and the novel S-plane controller. The effectiveness and feasibility of the novel S-plane controller established on sliding mode control in the AUV basic motion control is verified by the comparative analysis of experiment results.

Capsule endoscopy and panendoscopy:A journey to the future of gastrointestinal endoscopy

In 2000,the small bowel capsule revolutionized the management of patients with small bowel disorders.Currently,the technological development achieved by the new models of double-headed endoscopic capsules,as miniaturized devices to evaluate the small bowel and colon[pan-intestinal capsule endoscopy(PCE)],makes this non-invasive procedure a disruptive concept for the management of patients with digestive disorders.This technology is expected to identify which patients will require conventional invasive endoscopic procedures(colonoscopy or balloon-assisted enteroscopy),based on the lesions detected by the capsule,i.e.,those with an indication for biopsies or endoscopic treatment.The use of PCE in patients with inflammatory bowel diseases,namely Crohn’s disease,as well as in patients with iron deficiency anaemia and/or overt gastrointestinal(GI)bleeding,after a non-diagnostic upper endoscopy(esophagogastroduodenoscopy),enables an effective,safe and comfortable way to identify patients with relevant lesions,who should undergo subsequent invasive endoscopic procedures.The recent development of magnetically controlled capsule endoscopy to evaluate the upper GI tract,is a further step towards the possibility of an entirely non-invasive assessment of all the segments of the digestive tract,from mouth-to-anus,meeting the expectations of the early developers of capsule endoscopy.

A gated recurrent unit model to predict Poisson’s ratio using deep learning

Static Poisson’s ratio(vs)is crucial for determining geomechanical properties in petroleum applications,namely sand production.Some models have been used to predict vs;however,the published models were limited to specific data ranges with an average absolute percentage relative error(AAPRE)of more than 10%.The published gated recurrent unit(GRU)models do not consider trend analysis to show physical behaviors.In this study,we aim to develop a GRU model using trend analysis and three inputs for predicting n s based on a broad range of data,n s(value of 0.1627-0.4492),bulk formation density(RHOB)(0.315-2.994 g/mL),compressional time(DTc)(44.43-186.9 μs/ft),and shear time(DTs)(72.9-341.2μ s/ft).The GRU model was evaluated using different approaches,including statistical error an-alyses.The GRU model showed the proper trends,and the model data ranges were wider than previous ones.The GRU model has the largest correlation coefficient(R)of 0.967 and the lowest AAPRE,average percent relative error(APRE),root mean square error(RMSE),and standard deviation(SD)of 3.228%,1.054%,4.389,and 0.013,respectively,compared to other models.The GRU model has a high accuracy for the different datasets:training,validation,testing,and the whole datasets with R and AAPRE values were 0.981 and 2.601%,0.966 and 3.274%,0.967 and 3.228%,and 0.977 and 2.861%,respectively.The group error analyses of all inputs show that the GRU model has less than 5% AAPRE for all input ranges,which is superior to other models that have different AAPRE values of more than 10% at various ranges of inputs.

Design of TakagiSugeno fuzzy model based nonlinear sliding model controller

A design method is presented for Takagi-Sugeno （T-S） fuzzy model based nonlinear sliding model controller. First, the closed-loop fuzzy system is divided into a set of dominant local linear systems according to operating sub-regions. In each sub-region the fuzzy system consists of nominal linear system and a group of interacting systems. Then the controller composed two parts is designed. One part is designed to control the nominal system, the other is designed to control the interacting systems with sliding mode theory. The proposed controller can improve the robusmess and gnarantee tracking performance of the fuzzy system. Stability is guaranteed without finding a common positive definite matrix.

Unified Control Theory from PID to ACPID

To address the challenge of achieving unified control across diverse nonlinear systems, a comprehensive control theory spanning from PID (Proportional-Integral-Derivative) to ACPID (Auto-Coupling PID) has been proposed. The primary concept is to unify all intricate factors, including internal dynamics and external bounded disturbance, into a single total disturbance. This enables the mapping of various nonlinear systems onto a linear disturbance system. Based on the theory of PID control and the characteristic equation of a critically damping system, Zeng’s stabilization rules (ZSR) and an ACPID control force based on a single speed factor have been designed. ACPID control theory is both simple and practical, with significant scientific significance and application value in the field of control engineering.