Optimal full-order filtering for discrete-time systems with random measurement delays and multiple packet dropouts

This paper is concerned with the estimation problem for discrete-time stochastic linear systems with possible single unit delay and multiple packet dropouts. Based on a proposed uncertain model in data transmission, an optimal full-order filter for the state of the system is presented, which is shown to be of the form of employing the received outputs at the current and last time instants. The solution to the optimal filter is given in terms of a Riccati difference equation governed by two binary random variables. The optimal filter is reduced to the standard Kalman filter when there are no random delays and packet dropouts. The steady-state filter is also investigated. A sufficient condition for the existence of the steady-state filter is given. The asymptotic stability of the optimal filter is analyzed.

Improved H_∞ control for networked control systems with network-induced delay and packet dropout

The H_∞ performance analysis and controller design for linear networked control systems(NCSs) are presented.The NCSs are considered a linear continuous system with time-varying interval input delay by assuming that the sensor is time-driven and the logic Zero-order-holder(ZOH) and controller are event-driven.Based on this model,the delay interval is divided into two equal subintervals for H_∞ performance analysis.An improved H_∞ stabilization condition is obtained in linear matrix inequalities(LMIs) framework by adequately considering the information about the bounds of the input delay to construct novel Lyapunov–Krasovskii functionals(LKFs).For the purpose of reducing the conservatism of the proposed results,the bounds of the LKFs differential cross terms are properly estimated without introducing any slack matrix variables.Moreover,the H_∞ controller is reasonably designed to guarantee the robust asymptotic stability for the linear NCSs with an H_∞ performance level γ.Numerical simulation examples are included to validate the reduced conservatism and effectiveness of our proposed method.

Guaranteed Cost Active Fault-tolerant Control of Networked Control System with Packet Dropout and Transmission Delay

The problem of guaranteed cost active fault-tolerant controller （AFTC） design for networked control systems （NCSs） with both packet dropout and transmission delay is studied in this paper. Considering the packet dropout and transmission delay, a piecewise constant controller is adopted. With a guaranteed cost function, optimal controllers whose number is equal to the number of actuators are designed, and the design process is formulated as a convex optimal problem that can be solved by existing software. The control strategy is proposed as follows： when actuator failures appear, the fault detection and isolation unit sends out the information to the controller choosing strategy, and then the optimal stabilizing controller with the smallest guaranteed cost value is chosen. Two illustrative examples are given to demonstrate the effectiveness of the proposed approach. By comparing with the existing methods, it can be seen that our method has a better performance.

Stochastic stability of networked control systems with network-induced delay and data dropout

This paper deals with the stochastic stability of networked control systems with the presence of network- induced delay and transmitted data dropout. Based on the Lyapunov approach, sufficient conditions for the mean-square stability of the networked control system are derived subject that the sequence of transmission interval is driven by an identically independently distributed sequence and by a finite state Markov chain, respectively. Stabilization controllers are constructed in terms of linear matrix inequalities correspondingly. An example is provided to illustrate our results.

H_∞-based fault detection for nonlinear networked systems with random packet dropout and probabilistic interval delay

The fault detection problem for the nonlinear networked control system （NCS） with packet dropout and delay is investigated. A nonlinear stochastic system model is proposed to account for the NCS with random packet dropout and network- induced non-uniformly distributed time-varying delay in both from sensor to controller （S/C） and from controller to actuator （C/A）. Based on the obtained NCS model, employing an observer-based fault detection filter as the residual generator, the addressed fault detection problem is converted into an auxiliary nonlinear H∞ control problem. Then, with the help of Lyapunov functional approach, a sufficient condition for the desired fault detection filter is constructed in terms of certain linear matrix inequalities, which depend on not only the delay interval but also the delay interval occurrence rate and successful packet communication rate. Especially, a trade-off phenomenon between the maximum allowable delay bound and successful data packet transmission rate is found, which is typically resulted from the limited bandwidth of communication networks. The effectiveness of the proposed method is demonstrated by a simulation example.

Controller design for networked control system with data packet dropout and transmission delays

In this paper, the stabilization problem for a class of networked control systems （NCSs） with data packet dropouts and transmission time delays is considered, where the delays are time-varying and uncertain, the data packet dropout is modeled as a two-state Markov chain. To compensate the lost packet, a data packet dropout compensator is established. Thus a more realistic model for such NCSs is presented. Sufficient conditions for the stabilization of the new resulting system are derived in the form of linear matrix inequalities （LMIs）. Numerical example illustrates the solvability and effectiveness of the results.

Fault detection observer design for networked control system with long time-delays and data packet dropout

Focusing on the networked control system with long time-delays and data packet dropout,the problem of observerbased fault detection of the system is studied.According to conditions of data arrival of the controller,the state observers of the system are designed to detect faults when they occur in the system.When the system is normal,the observers system is modeled as an uncertain switched system.Based on the model,stability condition of the whole system is given.When conditions are satisfied,the system is asymptotically stable.When a fault occurs,the observers residual can change rapidly to detect the fault.A numerical example shows the effectiveness of the proposed method.

Packet-loss-dependent stabilization of NCSs with network-induced delay and packet dropout

This paper is concerned with controller design of net- worked control systems （NCSs） with both network-induced delay and arbitrary packet dropout. By using a packet-loss-dependent Lyapunov function, sufficient conditions for state/output feedback stabilization and corresponding control laws are derived via a switched system approach. Different from the existing results, the proposed stabilizing controllers design is dependent on the packet loss occurring in the last two transmission intervals due to the network-induced delay. The cone complementary lineara- tion （CCL） methodology is used to solve the non-convex feasibility problem by formulating it into an optimization problem subject to linear matrix inequality （LMI） constraints. Numerical examples and simulations are worked out to demonstrate the effectiveness and validity of the proposed techniques.

Impulsive controller design for nonlinear networked control systems with time delay and packet dropouts

The globally exponential stability of nonlinear impul- sive networked control systems （NINCS） with time delay and packet dropouts is investigated. By applying Lyapunov function theory, sufficient conditions on the global exponential stability are derived by introducing a comparison system and estimating the corresponding Cauchy matrix. An impulsive controller is explicitly designed to achieve exponential stability and ensure state con- verge with a given decay rate for the system. The Lorenz oscillator system is presented as a numerical example to illustrate the theo- retical results and effectiveness of the proposed controller design procedure.

Diagnostic delay in inflammatory bowel diseases in a German population

BACKGROUND Early diagnosis is key to prevent bowel damage in inflammatory bowel disease(IBD).Risk factor analyses linked with delayed diagnosis in European IBD patients are scarce and no data in German IBD patients exists.AIM To identify risk factors leading to prolonged diagnostic time in a German IBD cohort.METHODS Between 2012 and 2022,430 IBD patients from four Berlin hospitals were enrolled in a prospective study and asked to complete a 16-item questionnaire to determine features of the path leading to IBD diagnosis.Total diagnostic time was defined as the time from symptom onset to consulting a physician(patient waiting time)and from first consultation to IBD diagnosis(physician diagnostic time).Univariate and multivariate analyses were performed to identify risk factors for each time period.RESULTS The total diagnostic time was significantly longer in Crohn’s disease(CD)compared to ulcerative colitis(UC)patients(12.0 vs 4.0 mo;P<0.001),mainly due to increased physician diagnostic time(5.5 vs 1.0 mo;P<0.001).In a multivariate analysis,the predominant symptoms diarrhea(P=0.012)and skin lesions(P=0.028)as well as performed gastroscopy(P=0.042)were associated with longer physician diagnostic time in CD patients.In UC,fever was correlated(P=0.020)with shorter physician diagnostic time,while fatigue(P=0.011)and positive family history(P=0.046)were correlated with longer physician diagnostic time.CONCLUSION We demonstrated that CD patients compared to UC are at risk of long diagnostic delay.Future efforts should focus on shortening the diagnostic delay for a better outcome in these patients.

基于SEAIQR模型与Dropout-LSTM模型的西安市COVID-19疫情趋势预测

目的基于传染病动力学SEAIQR(susceptible-exposed-asymptomatic-infected-quarantined-removed)模型和Dropout-LSTM(Dropout long short term memory network)模型预测西安市新型冠状病毒肺炎(COVID-19)疫情的发展趋势,为评估“动态清零”策略防控效果提供科学依据。方法考虑到西安市本轮疫情存在大量的无症状感染者、依时变化的参数以及采取的管控举措等特点,构建具有阶段性防控措施的时变SEAIQR模型。考虑到COVID-19疫情数据的时序性特征及它们之间的非线性关系,构建深度学习Dropout-LSTM模型。选用2021年12月9日-2022年1月31日西安市新增确诊病例数据进行拟合,用2022年2月1日-2022年2月7日数据评估预测效果,计算有效再生数(R_(t))并评价不同参数对疫情发展的影响。结果SEAIQR模型预测的新增确诊病例拐点预计在2021年12月26日出现,约为176例,疫情将于2022年1月24日实现“动态清零”,模型R^(2)=0.849。Dropout-LSTM模型能够体现数据的时序性与非线性特征,预测出的新增确诊病例数与实际情况高度吻合,R^(2)=0.937。Dropout-LSTM模型的MAE和RMSE均较SEAIQR模型低,说明预测结果更为理想。疫情暴发初期,R 0为5.63,自实施全面管控后,R_(t)呈逐渐下降趋势,直到2021年12月27日降至1.0以下。随着有效接触率不断缩小、管控措施的提早实施及免疫阈值的提高,新增确诊病例在到达拐点时的人数将会持续降低。结论建立的Dropout-LSTM模型实现了较准确的疫情预测,可为COVID-19疫情“动态清零”防控决策提供借鉴。

Prescribed Performance Tracking Control of Time-Delay Nonlinear Systems With Output Constraints

The problem of prescribed performance tracking control for unknown time-delay nonlinear systems subject to output constraints is dealt with in this paper. In contrast with related works, only the most fundamental requirements, i.e., boundedness and the local Lipschitz condition, are assumed for the allowable time delays. Moreover, we focus on the case where the reference is unknown beforehand, which renders the standard prescribed performance control designs under output constraints infeasible. To conquer these challenges, a novel robust prescribed performance control approach is put forward in this paper.Herein, a reverse tuning function is skillfully constructed and automatically generates a performance envelop for the tracking error. In addition, a unified performance analysis framework based on proof by contradiction and the barrier function is established to reveal the inherent robustness of the control system against the time delays. It turns out that the system output tracks the reference with a preassigned settling time and good accuracy,without constraint violations. A comparative simulation on a two-stage chemical reactor is carried out to illustrate the above theoretical findings.

基于Bi-LSTM-Dropout的蓄电池剩余使用寿命预测方法

蓄电池剩余使用寿命预测对能源的安全性和可持续发展至关重要。该文提出一种蓄电池剩余使用寿命的预测方法,利用蓄电池的历史运行数据和充放电周期,构建Bi-LSTM-Dropout网络模型。利用Bi-LSTM提取时间序列中蓄电池长期依赖的特征,采用Dropout优化算法降低Bi-LSTM网络模型的复杂度,提高模型的泛化能力。实验结果表明,该方法在测试集上的准确率达96.2%,实现了蓄电池剩余使用寿命的精确预测。

基于添加Dropout层的CNN-LSTM网络短期负荷预测

精准的短期负荷预测能帮助电力部门制订合理的生产调度计划,达到节省能源消耗的目的。为提升短期负荷预测的准确性,提出一种添加Dropout层的CNN-LSTM网络短期负荷预测方法。首先,根据电力负荷预测流程对预测的影响因素如气象、日期类型等进行相关性验证后构建输入特征向量;其次,使用一维卷积网络对输入的特征向量进行卷积、池化处理,并在LSTM网络全连接层添加Dropout层进行短期负荷预测仿真实验;最后,使用某电网历史数据进行测试。结果表明,相比于单独的LSTM网络,所建模型对短期负荷的预测效果更好。

One memristor–one electrolyte-gated transistor-based high energy-efficient dropout neuronal units

Artificial neural networks(ANN) have been extensively researched due to their significant energy-saving benefits.Hardware implementations of ANN with dropout function would be able to avoid the overfitting problem. This letter reports a dropout neuronal unit(1R1T-DNU) based on one memristor–one electrolyte-gated transistor with an ultralow energy consumption of 25 p J/spike. A dropout neural network is constructed based on such a device and has been verified by MNIST dataset, demonstrating high recognition accuracies(> 90%) within a large range of dropout probabilities up to40%. The running time can be reduced by increasing dropout probability without a significant loss in accuracy. Our results indicate the great potential of introducing such 1R1T-DNUs in full-hardware neural networks to enhance energy efficiency and to solve the overfitting problem.

Attosecond ionization time delays in strong-field physics

Electronic processes within atoms and molecules reside on the timescale of attoseconds. Recent advances in the laserbased pump-probe interrogation techniques have made possible the temporal resolution of ultrafast electronic processes on the attosecond timescale, including photoionization and tunneling ionization. These interrogation techniques include the attosecond streak camera, the reconstruction of attosecond beating by interference of two-photon transitions, and the attoclock. While the former two are usually employed to study photoionization processes, the latter is typically used to investigate tunneling ionization. In this review, we briefly overview these timing techniques towards an attosecond temporal resolution of ionization processes in atoms and molecules under intense laser fields. In particular, we review the backpropagation method, which is a novel hybrid quantum-classical approach towards the full characterization of tunneling ionization dynamics. Continued advances in the interrogation techniques promise to pave the pathway towards the exploration of ever faster dynamical processes on an ever shorter timescale.

Examining the association between delay discounting,delay aversion and physical activity in Chinese adults with type-2 diabetes mellitus

BACKGROUND The role of physical activity in diabetes is critical,influencing this disease's development,man-agement,and overall outcomes.In China,22.3%of adults do not meet the minimum level of physical activity recommended by the World Health Organization.Therefore,it is imperative to identify the factors that contributing to lack of physical activity must be identified.AIM To investigate the relationship among delay discounting,delay aversion,glycated hemoglobin(HbA1c),and various levels of physical activity in Chinese adults diagnosed with type 2 diabetes mellitus(T2DM).METHODS In 2023,400 adults with T2DM were recruited from the People's Hospital of Linxia Hui Autonomous Prefecture of Gansu Province.A face-to-face questionnaire was used to gather demographic data and details on physical activity,delay discounting,and delay aversion.In addition,HbA1c levels were measured in all 400 participants.The primary independent variables considered were delay discounting and delay aversion.The outcome variables included HbA1c levels and different intensity levels of physical activity,including walking,moderate physical activity,and vigorous physical activity.Multiple linear regression models were utilized to assess the relationship between delay discounting,delay aversion,and HbA1c levels,along with the intensity of different physical activity measured in met-hours per week.RESULTS After controlling for the sample characteristics,delay discounting was negatively associated with moderate physical activity(β=-2.386,95%CI:-4.370 to-0.401).Meanwhile,delay aversion was negatively associated with the level of moderate physical activity(β=-3.527,95%CI:-5.578 to-1.476)in the multiple linear regression model,with statistically significant differences.CONCLUSION Elevated delay discounting and increased delay aversion correlated with reduced levels of moderate physical activity.Result suggests that delay discounting and aversion may influence engagement in moderate physical activity.This study recommends that health administration and government consider delay discounting and delay aversion when formulating behavioral intervention strategies and treatment guidelines involving physical activity for patients with T2DM,which may increase participation in physical activity.This study contributes a novel perspective to the research on physical activity in adults with T2DM by examining the significance of future health considerations and the role of emotional responses to delays.

Spectrum of delayed post-hypoxic leukoencephalopathy syndrome:A systematic review

BACKGROUND Delayed post hypoxic leukoencephalopathy syndrome(DPHLS),also known as Grinker’s myelinopathy,is a rare but significant neurological condition that manifests days to weeks after a hypoxic event.Characterized by delayed onset of neurological and cognitive deficits,DPHLS presents substantial diagnostic and therapeutic challenges.AIM To consolidate current knowledge on pathophysiology,clinical features,diagnostic approaches,and management strategies for DPHLS,providing a comprehensive overview and highlighting gaps for future research.METHODS Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyzes guidelines,we systematically searched PubMed,ScienceDirect and Hinari databases using terms related to delayed post-hypoxic leukoencephalopathy.Inclusion criteria were original research articles,case reports,and case series involving human subjects with detailed clinical,neuroimaging,or pathological data on DPHLS.Data were extracted on study characteristics,participant demographics,clinical features,neuroimaging findings,pathological findings,treatment,and outcomes.The quality assessment was performed using the Joanna Briggs Institute critical appraisal checklist.RESULTS A total of 73 cases were reviewed.Common comorbidities included schizoaffective disorder,bipolar disorder,hypertension,and substance use disorder.The primary causes of hypoxia were benzodiazepine overdose,opioid overdose,polysubstance overdose,and carbon monoxide(CO)poisoning.Symptoms frequently include decreased level of consciousness,psychomotor agitation,cognitive decline,parkinsonism,and encephalopathy.Neuroimaging commonly revealed diffuse T2 hyperintensities in cerebral white matter,sometimes involving the basal ganglia and the globus pallidus.Magnetic resonance spectroscopy often showed decreased N-acetylaspartate,elevated choline,choline-to-creatinine ratio,and normal or elevated lactate.Treatment is often supportive,including amantadine,an antioxidant cocktail,and steroids.Hyperbaric oxygen therapy may be beneficial in those with CO poisoning.Parkinsonism was often treated with levodopa.Most of the patients had substantial recovery over the course of months and many cases had some residual neurocognitive deficits.CONCLUSION DPHLS remains a complex and multifaceted condition with various etiologies and clinical manifestations.Early recognition and appropriate management are crucial to improving patient outcomes.Future research should focus on standardizing diagnostic criteria,using advanced imaging techniques,and exploring therapeutic interventions to improve understanding and treatment of DPHLS.Conducting prospective cohort studies and developing biomarkers for early diagnosis and monitoring will be essential to advance patient care.

Surgical techniques to prevent delayed gastric emptying after pancreaticoduodenectomy

Background: Delayed gastric emptying(DGE) is one of the most common complications after pancreaticoduodenectomy(PD). DGE represents impaired gastric motility without significant mechanical obstruction and is associated with an increased length of hospital stay, increased healthcare costs, and a high readmission rate. We reviewed published studies on various technical modifications to reduce the incidence of DGE. Data sources: Studies were identified by searching Pub Med for relevant articles published up to December 2022. The following search terms were used: “pancreaticoduodenectomy”, “pancreaticojejunostomy”, “pancreaticogastrostomy”, “gastric emptying”, “gastroparesis” and “postoperative complications”. The search was limited to English publications. Additional articles were identified by a manual search of references from key articles. Results: In recent years, various surgical procedures and techniques have been explored to reduce the incidence of DGE. Pyloric resection, Billroth II reconstruction, Braun's enteroenterostomy, and antecolic reconstruction may be associated with a decreased incidence of DGE, but more high-powered studies are needed in the future. Neither laparoscopic nor robotic surgery has demonstrated superiority in preventing DGE, and the use of staplers is controversial regarding whether they can reduce the incidence of DGE. Conclusions: Despite many innovations in surgical techniques, there is no surgical procedure that is superior to others to reduce DGE. Further larger prospective randomized studies are needed.

Analysis and Design of Time-Delay Impulsive Systems Subject to Actuator Saturation

This paper investigates the exponential stability and performance analysis of nonlinear time-delay impulsive systems subject to actuator saturation. When continuous dynamics is unstable, under some conditions, it is shown that the system can be stabilized by a class of saturated delayed-impulses regardless of the length of input delays. Conversely, when the system is originally stable, it is shown that under some conditions, the system is robust with respect to sufficient small delayed-impulses. Moreover, the design problem of the controller with the goal of obtaining a maximized estimate of the domain of attraction is formulated via a convex optimization problem. Three examples are provided to demonstrate the validity of the main results.