Control Design Research Articles

Sampled‐data‐driven event‐triggered secure control of uncertain nonlinear cyber‐physical systems against multiple attacks

AbstractIn this paper, the sampled‐data‐driven event‐triggered secure control is discussed for a class of uncertain nonlinear cyber‐physical systems under multiple attacks containing deception attacks and replay attacks. Compared with exisiting research, the studied systems take into account the uncertainty and coupling that may occur in practical situations. Notably, deception attacks impede the application of a gain design approach in control design. To address this issue, an artful state transformation is presented to convert the considered system into an auxiliary system. Based on this, a novel sampled‐data‐driven attack compensation scheme is devised via the gain design approach, and an event‐triggered mechanism is further introduced into the scheme to cancel needless control updates, which successfully ensures state convergence meanwhile resisting the impact of multiple attacks. Particularly, the designed control scheme not only utilizes data efficiently but also avoids Zeno behaviour automatically by judging triggering conditions in sampled points. Finally, the validity of the results is verified through two simulation examples.

Online decoupling of the time-varying longitudinal feedback loops for improved performance in Advanced Virgo Plus*

Abstract Gravitational Wave detectors require low-noise sensors combined with high-performance feedback loops to maximize the detector sensitivity in the low-frequency detection range. Some feedback loops in the detector are strongly coupled and their coupling varies over time, which is inherent to the optical configuration and the optical readout scheme used to obtain error signals for the feedback loops. This paper presents a control-based approach to deal with the time-varying interaction among three of the longitudinal degrees of freedom in the Advanced Virgo Plus detector, using the pre-existing infrastructure of the detector. An intuitive Multiple-Input Multiple-Output stability criterion is presented that illustrates how the time-varying coupling affects the stability of the feedback loops, as well as a method that identifies the coupling online and updates a decoupling matrix accordingly. Experiment results of the proposed method on the Advanced Virgo Plus detector illustrate continuous minimization of the coupling over time. Using the derived stability criterion, it is furthermore shown that the coupling is sufficiently minimized such that the interaction terms can be neglected in the control design, resulting in an improved controller performance.

The Supplemental Nutrition Program for Women, Infants, and Children and Birth Outcomes Among Hispanic Mothers in California: A Sibling Control Design.

Participation in the Supplemental Nutrition Program for Women, Infants, and Children (WIC) during pregnancy appears to reduce risks of preterm birth and low birthweight. Many pregnant women who receive WIC benefits, however, also participate in Medicaid (Medi-Cal in California). This co-participation raises the question of whether WIC per se confers these perinatal health benefits. We use a unique, sibling-linked dataset of California births to estimate birth outcomes relating to program receipt (i.e., No WIC or Medi-Cal; WIC alone; Medi-Cal alone; and WIC and Medi-Cal). We also contribute to the literature by focusing on Hispanic mothers who represent the largest fraction of births in California, as well as the highest proportion of WIC recipients in the state. We specifically assessed the relation of differential program receipt on preterm birth (< 37weeks) and low birthweight (< 2500g). We restrict our analytic sample to births between 2007 and 2015 (n = 942,274). Our sibling-control results show lower odds of low birthweight (OR: 0.82, 95% CI: 0.77, 0.87) and preterm birth (OR: 0.87, 95% CI: 0.83, 0.90) when Hispanic mothers receive WIC benefits during pregnancy compared to when the mothers do not receive WIC benefits. While births associated with receipt of both WIC and Medi-Cal also exhibit lower odds of preterm birth (OR: 0.86, 95% CI: 0.79, 0.92), the protective findings do not extend to low birthweight. Our results extend previous work in other states and should stimulate additional research on whether participation in multiple means-tested programs reduce racial/ethnic disparities in adverse birth outcomes.

Yoga Intervention and Inflammatory Homoeostasis in Breast Cancer Patients

Objectives: Yoga, renowned for its ability to maintain physical, mental and spiritual well-being, has recently gained prominence as a supportive therapy during conventional breast cancer (BC) treatment. This paradigm shift reflects a growing trend of people embracing yoga to enhance their overall health and aid in managing BC. The objective of this study was to determine the yoga intervention and inflammatory homoeostasis in newly diagnosed BC patients. Materials and Method: This study recruited 44 newly diagnosed BC patients at stages II, III and IV (without distant metastasis or other inflammatory diseases), all admitted for neoadjuvant chemotherapy followed by surgery. A prospective non-randomised control design was employed. Baseline assessments were conducted before the first chemotherapy cycle, with follow-ups before the 2nd and 3rd chemotherapy cycles, before surgery, and 2 months post-surgery. The outcome was compared with the control group. Results: The study showed significant within-subject effects in the yoga intervention group on serum tumour necrosis factor-alpha, interleukin (IL)-1-beta and IL-6 levels, while no significant changes were observed in the control group. Although between groups did not show statistically significant, the mean values indicated a consistent downregulation of proinflammatory markers over time in the yoga group. Conclusion: Incorporating yoga as a complementary therapy alongside conventional BC treatment significantly improved the health outcomes of BC patients by modulating proinflammatory markers.

Repair overlays of modified polymer mortar containing glass powder and composite fibers-reinforced slag: mechanical properties, energy absorption, and adhesion to substrate concrete

This article aims to investigate the mechanical properties and substrate adhesion of the pull-off method in polymer mortars modified with styrene-butadiene resin polymer (SBR) containing glass powder and composite fiber-reinforced slag. Different mix designs were investigated with and without SBR, taking into account different amounts of glass powder and slag separately and in combination, along with the effect of glass, polypropylene, and steel fibers alone and in combination. The flexural performance and energy absorption of beams retrieved with these layers were also assessed. The results revealed significant differences and increases in the substrate adhesion of the restored modified polymer layers containing SBR compared to the polymer-free repair overlays. Furthermore, an improvement was observed in the adhesion performance of the repair overlay using a combination of slag and glass powder and the glass and polypropylene fiber composite. The highest adhesion was related to the modified polymer mortar design containing composite fibers of glass, polypropylene, and steel with 25% replacement of SBR polymer for 10% glass powder, 10% slag, and 5% slag with 5% glass powder. The adhesion was increased by about 3.74, 3.72, and 3.78 times compared to the repair overlay of the control design. Modified polymer mortars had a higher T150D toughness. Moreover, the energy absorption was significantly improved by the presence of SBR polymer. The highest toughness values were found in the beams restored with modified polymer mortars containing polypropylene, glass, and steel composite fibers with an increase of 48.51%–66.42% compared to the samples without polymer as a result of the pozzolans used in this mix.

Adaptive fuzzy coordinated control design for wind turbine using gray wolf optimization algorithm

Due to the randomness and intermittency of wind speed, the actual output power curve of a wind turbine (WT) deviates greatly from the theoretical power curve, thereby reducing the power generation capacity of the WT. An adaptive fuzzy coordinated control (AFCC) of WT is presented in this study to improve the power generation of WT. Firstly, a multi-objective optimization model (MOOM) for WT output power, generator speed and pitch angle is established, and its optimal solution set is used as the input eigenvector of a novel effective wind speed soft sensor (NEWSSS) model, which is modeled with kernel extreme learning machine (KELM). Secondly, a novel improved gray wolf optimization (NIGWO) algorithm is presented by improving the convergence factor and adaptive weights, which is used to solve MOOM and optimize the parameters of KELM. A variable pitch control (VPC) is designed by estimating the effective wind speed. Finally, an adaptive fuzzy control (AFC) is presented for WT. Based on the AFC and VPC, an AFCC for pitch angle and generator torque is designed for WT. The high measuring precision of NEWSSS and the good robustness and dynamic performance of AFCC are demonstrated by the simulation results.

A Simplified Dynamic Model of DFIG-based Wind Generation for Frequency Support Control Studies

In recent years, wind generation has been fast growing and become one of the major generation resources in power systems. Since the wind generation does not inherently equip with frequency support functions, the power system frequency response degrades as the wind penetration increases. Therefore, frequency support control of wind generation has gained increasing focus. However, the dynamic models of wind generation systems, which are required by the control design and analysis, are commonly very complicated and difficult to obtain, especially for the doubly-fed induction generator based wind turbine (DFIG-WT). In this paper, the authors propose a simplified dynamic model for the DFIG-WT. The proposed analytical model is derived from the detailed model by selectively neglecting very fast dynamics while keeping the critical ones. It is suitable for frequency control studies. The model accuracy is first validated against the detailed DFIG-WT model in Simulink. Then, the wind frequency control function is studied based on the proposed model.

Inverse design of acoustic metamaterial-based vibration control for offshore wind turbines

This paper presents an inverse design approach for mechanical metamaterial turbines utilising a deep learning algorithm. We first establish a theoretical model for metamaterial turbines using the spectral element method to analyse their vibration characteristics. Subsequently, we predict the vibration transmission properties of these turbines and achieve on-demand inverse design of metastructures through a fully connected deep-learning neural network model. The efficacy of the forward prediction and reverse design network models is validated using an inverse neural network. Our results demonstrate a strong agreement between the predicted and target values, affirming the feasibility of employing deep learning for on-demand meta-turbine design. This intelligent design approach holds promise for expediting and enhancing the design of metamaterials tailored for low-frequency vibration isolation in engineering structures.

Proteomic Profile of Blood Plasma of Mus Musculus in the Acute Toxicity Test of Single Black Garlic (Allium Sativum)

This study aims to obtain overall information about all proteins formed in body fluids, cells, or tissues at a certain time and to analyze the mechanism of cell responses to various types of stress and drugs. Single black garlic (SBG) has the potential to be a pharmacological agent. However, the safety of using single black garlic is still unknown, so a material toxicity test is needed. This research is a laboratory experimental research with a post-test-only control group design. An oral acute toxicity test was used. Observation time was 14 days and consisted of four treatments, negative control, SBG dose 2000 mg/kgbw (P1), 3000 mg/kgbw (P2), and 5000 mg/kgbw (P3). Post-treatment protein analysis was done using the SDS-PAGE electrophoresis method. Observations of clinical symptoms of SBG at doses of 2000 mg/kgbw, 3000 mg/kgbw, and 5000 mg/kgbw showed no clinical symptoms in mice, both motor activity and pupils were still normal, no convulsions (seizures), lacrimation, paralysis or death were seen in mice. Observations on plasma proteins showed differences in protein between the treatments at the SBG dose of 2000 mg/kgbw with the SBG dose of 3000 mg/kgbw and 5000 mg/kgbw, but the four treatments have the same type of protein in the protein band with a molecular weight of 25 kDa. So, it can be concluded that SBG doses of 2000 mg/kgbw, 3000 mg/kgbw, and 5000 mg/kgbw are not toxic to mice but can stimulate the expression of certain proteins. Keywords: Single Black garlic (SBG), oral acute toxicity test, proteomic analysis, SDS-PAGE

Feedforward Control Strategy of a DC-DC Converter for an Off-Grid Hydrogen Production System Based on a Linear Extended State Observer and Super-Twisting Sliding Mode Control

With the large-scale integration of renewable energy into off-grid DC systems, the stability issues caused by their fluctuations have become increasingly prominent. The dual active bridge (DAB) converter, as a DC-DC converter suitable for high power and high voltage level off-grid DC systems, plays a crucial role in maintaining and regulating grid stability through its control methods. However, the existing control methods for DAB are inadequate: linear control fails to meet dynamic response requirements, while nonlinear control relies on detailed model structures and parameters, making the control design complex and less accurate. To address this issue, this paper proposes a feedforward control strategy for a DC-DC converter in an off-grid hydrogen production system based on a linear extended state observer (LESO) and super-twisting sliding mode control (STSMC). Firstly, a reduced-order simplified model of the DAB was constructed through the structure of DAB. Then, based on the reduced-order simplified model, a feedforward control based on LESO and STSMC was designed, and its stability was analyzed. Finally, a simulation comparison of PI, LESO + terminal sliding mode control (TSMC), and LESO + STSMC control methods was conducted in a DC off-grid hydrogen production system. The results verified the proposed control method’s enhancement of the DAB’s rapid dynamic response capability and the system’s transient stability.

Randomized Controlled Trial to Evaluate the Efficacy of Positive Mental Health Program for Adults: Study Protocol.

To evaluate the effectiveness of a positive mental health program for adults (PMHP) in the community. Positive mental health (PMH) can be seen as a construct represented by six factors (personal satisfaction, prosocial attitude, self-control, autonomy, problem resolution, and self-actualization, and interpersonal relationship skills) according to the Multifactorial Model for PMH. Although there are several interventions in promoting mental health, research on effective promotion of PMH for adults in the community with structured and validated programs of PMH is scarce. This study protocol describes a randomized controlled trial (RCT) following a wait-list control design, aimed at evaluating the effectiveness of a PMHP in the community. This study was approved in June 2019 by the Ethics Committee. Participants will be recruited from the school community of teachers. Participants aged ≥ 18 years. The participants will be randomized 1:1 to either (a) an intervention group, which will integrate the PMHP, or (b) the standby control group. Three assessment moments for both groups will take place initial, after the intervention, and a follow-up of 3-6 months. The evaluation instruments will include a sociodemographic questionnaire, a PMH questionnaire, and a psychological vulnerability scale. The current study provides an innovative approach to PMH. Further, the study may demonstrate new interventions in PMH in the community, based on a program with systematized guidelines and sessions structured according to individual needs. It is expected that at the end of the program, the experimental group will increase the level of PMH. To allow future official implementation of the PMH program and the replication of the study in other professional groups as a promotion tool. There was no funding to remunerate a participant for this study. ClinicalTrials.gov identifier: NCT04600401. Registered on May 15, 2020.

A-202 Quality control design survey reveals 399 ways to do it wrong

Abstract Background The effectiveness of statistical quality control processes to detect unacceptable patient risk depends on the choices that laboratory professionals make for the design of quality control charts and acceptable patient risk. Recommended best practice consists of putting a meaningful recent mean and SD on the QC chart, selecting rules based on the method’s margin for error to unacceptable risk or Sigma value, and basing acceptable risk on clinical need. Methods A survey was circulated through LinkedIn and Labvine. Forty respondents who included their credentials were included in the final analysis. Respondents were asked to select the one most correct answer four questions regarding the parameters that govern the effectiveness of quality control processes. 1. The best source of the mean on the QC chart? (Four choices) 2. Best source of the SD on the QC chart? (Five choices) 3. Best way to select QC rules for each QC sample? (Six choices) 4. If an analytical process “fails,” we should stop reporting before [errors are reported.] (Five choices) A total of 400 potential patterns of QC selections were chosen. (4 * 5 * 5 * 4). Results When asked acceptable error rate if an analytical process “fails,” responses were More than 5% errors are reported - 11%. Any errors are reported - 66% It varies with clinical use of the test - 16% It varies with capabilities of our method - 8% While most respondents chose at least one of the recommended answers for QC chart design and rules, only three chose the best choice for all parameters. Conclusions Despite decades of recommendations of best practice for quality control, typical practice throughout the laboratory community in general does not reflect this. It is time to consider a new approach to teaching, validating and certifying competency in medical laboratory quality control.

Sliding mode control design using a generalized reduced-order fractional model for chemical processes

This article presents a comprehensive study that evaluates the potential advantages of adopting a unified, systematic, and organized general fractional model within the Sliding Mode Control (SMC) design framework. The exploration extends to the model's applicability in a variety of disciplines. Although prior research has utilized SMC and fractional-order systems independently, no previous work has established a mathematical framework that integrates a generic fractional-order SMC model. The study addresses this gap and highlights potential implications for control design and applications in a variety of fields, particularly for chemical processes.

A comprehensive control paradigm for prescribed performance attainment in complex nonlinear systems

This paper presents a comprehensive control framework tailored for achieving Prescribed Performance Control (PPC) in the context of complex nonlinear systems, addressing multifaceted challenges prevalent in control design. The focus is on a control scenario characterized by the simultaneous presence of nonlinearity, external disturbances, time delay, and unknown control direction—issues that pose considerable obstacles for existing solutions. To surmount these challenges, our proposed approach integrates well-established techniques, including neural networks, Nussbaum-type gains, and adaptive control strategies within a unified control design framework. The specific technical challenge addressed in this work involves the effective management of these intricate complexities in Single-Input Single-Output (SISO) systems. Our contributions extend the theoretical foundations, presenting an ideal PPC control design and introducing two adaptive neural network-based control methods capable of accommodating both known and unknown control directions. Utilizing Lyapunov–Krasovskii functionals, we showcase a unique integration that surpasses a mere combination of individual techniques. This work advances the theoretical underpinnings of control engineering tailored for real-world scenarios. The proposed controller’s efficacy is validated through rigorous simulations and compared with recent results and benchmark PPC controllers, establishing its superiority in addressing the intricacies of complex control scenarios.

Fuzzy approximation-based reparametrization and adaptive control design of nonlinear aircraft dynamics

This paper conducts a new study on fuzzy approximation-based reparametrization and adaptive control design of non-canonical nonlinear aircraft dynamics, with particular focus on emphasizing the expansion of linearization-based adaptive flight control designs from local to semi-global scopes. The linearization-based adaptive control method has been employed for managing non-canonical nonlinear aircraft systems, owing to its capability in handling the complexity of aircraft system dynamics. To enhance the operational range of the linearization-based approach, this paper focuses on the aircraft longitudinal dynamic model in general non-canonical forms. A semi-global linearization-based adaptive control method is developed for this kind of system. Firstly, a new reparametrization is devised, leveraging local linearized models and a concept of relative degree. Subsequently, adaptive controllers are designed to guarantee stable and asymptotic output tracking for aircraft systems with various relative degrees. The efficiency of the newly developed adaptive control approach is validated through simulation outcomes.

Zeolite‐Based Materials for Catalytic Oxidation of Volatile Organic Compounds

AbstractOwing to the structural stability, modifiable acidity, and abundant pores/channels, zeolite‐based materials can act as catalysts or supports for effective conversion of volatile organic compounds (VOCs). In this review, a series of VOC oxidation processes catalyzed by zeolite‐based materials will be introduced, which include thermal oxidation, photocatalytic degradation, plasma‐driven removal, catalytic ozonation, microwave‐assisted degradation, and hybrid systems, where the specific roles, modification strategies, and structure–performance relationships of zeolites are discussed in depth. The following topics will also be covered, including the catalytic mechanisms of VOC oxidation, types of zeolite‐based materials in VOC catalytic oxidation, operation parameters in the processes, and reactor designs for efficiency optimization and cost control.

Numerical simulation of gravel packing in multi-branch horizontal wells in hydrate reservoirs based on CFD-DEM coupling

The current single-wellbore gravel packing completion method for hydrate production is limited by its narrow pressure reduction range, leading to reduced production capacity in later stages. To address this, the "branch horizontal well completion with full-wellbore gravel packing and sand control" method has been proposed to significantly expand the pressure reduction range and enhance natural gas production. However, there is a lack of comprehensive studies on gravel packing in branch horizontal wells, the construction design for gravel packing and sand control in branch horizontal wells lacks a solid theoretical foundation. In this study, we establish a CFD-DEM coupled model to simulate gravel packing in single and multi-branch horizontal wellbores, accurately capturing particle movement. We investigate the effects of injection rate, gravel concentration, branch wellbore length, and branch wellbore angle on gravel packing efficiency. The five distinct stages of gravel packing in branch horizontal wells are elucidated. Results indicate that increasing the fluid injection rate, reducing sand concentration, and decreasing both the length and angle of the branch wellbore can significantly improve the packing efficiency. Notably, the filling ratio in the branch wellbore at an angle of 15° was 11.42% higher than that at 30°; As the length of the branch wellbore increases from 1m to 2m, the filling ratio of the branch wellbore decreases significantly. We recommend utilizing a high injection rate (0.6 m³/min), low gravel concentration (3%) to optimize the filling ratio and compaction in both the main and branch wellbores.

Design of Intelligent Control Under Machine Learning Supervision and Signal Compression Mechanism Design for NCSs Under DoS Attacks

Design of Intelligent Control Under Machine Learning Supervision and Signal Compression Mechanism Design for NCSs Under DoS Attacks

Design and Tank Testing of Reinforcement Learning Control for Wave Energy Converters

Design and Tank Testing of Reinforcement Learning Control for Wave Energy Converters

Design and Analysis of the Model Predictive Control Implemented by the ANN Technique for MMC-Based Rectifier With Improved Grid Adaptability

Design and Analysis of the Model Predictive Control Implemented by the ANN Technique for MMC-Based Rectifier With Improved Grid Adaptability