Control Approach Research Articles

Study on stable thrust of separated undulating fins

Constrained by their inherent motion characteristics, undulating fins generate fluctuating thrust during movement, which is disadvantageous for precise underwater positioning and control. Drawing inspiration from the principles of biomimicry and leveraging the excellent maneuverability and propulsion capabilities of dragonflies, this study establishes a separated undulating fins model based on the dragonfly's unique front and rear wing structures. The impact of different phases of the separated undulating fins on thrust is studied by numerical simulation methods and quantitatively evaluate thrust stability using the range and standard deviation. Refining relevant theoretical derivations, the mapping relationship between the phase and thrust stability is established. The intrinsic mechanism behind the generation of stable thrust by separated undulating fins is revealed through flow field analysis. A new undulating fin validation platform is designed and constructed, with experimental results demonstrating a good concordance with numerical simulation outcomes. The study reveals that separated undulating fins can effectively reduce thrust fluctuations, with the range of thrust being only 48% of that of traditional undulating fins and the standard deviation being only 35% of that of traditional undulating fins. This research provides a novel approach and theoretical support for the precise control of underwater robots equipped with undulating fins.

Wage patterns in West Berlin: a synthetic control approach after the fall of the wall

ABSTRACT We investigate the impact of the Berlin Wall’s fall on West Berliners’ salaries using the Synthetic Control Method and regional-level data (NUTS-2) from the German Socio-Economic Panel (SOEP). Our study shows that the collapse of the Berlin Wall led to a sudden stagnation in salaries for West Berliners, compared to a scenario where the Wall had remained intact.

Performance of Robust Type-2 Fuzzy Sliding Mode Control Compared to Various Conventional Controls of Doubly-Fed Induction Generator for Wind Power Conversion Systems

This paper presents a novel hybrid type-2 fuzzy sliding mode control approach for regulating active and reactive power exchanged with the utility grid by a doubly-fed induction generator in a wind energy conversion system. The main objective of this hybridization is to eliminate the steady-state chattering phenomenon inherent in sliding mode control while improving the transient delays caused by type-2 fuzzy controllers. In addition, the proposed control approach has proven to be successful in coping with varying generator parameters and exhibited good reference tracking. An in-depth comparative study with state-of-the-art advanced control techniques is also the focus of the present paper. The comparative study has three objectives, namely: a qualitative comparative study that aims to compare response times and reference tracking capabilities; a quantitative evaluation that takes into account time-integrated performance criteria; and finally, robustness capabilities. The simulation results, carried out in the Matlab/Simulink environment, have demonstrated the effectiveness and best performance of the proposed hybrid type-2 fuzzy sliding mode control with respect to other advanced techniques included in the comparison study.

Plasma-modified Co3O4 nanosheets for efficient CO detection: Insight into the structure-activity relationship

Exploring the correlation between crucial reactive sites and surface electron structure in the sensitive layer of gas sensors can achieve simultaneous optimization of kinetics and thermodynamics. In this work, Ar and O2 plasma sputtering are used to study how varying levels of Co3+ and oxygen vacancy affect the gas-sensitivity of Co3O4. The gas-sensing performance of Co3O4-O2PT (O2 plasma sputtering) is better than that of Co3O4-ArPT (Ar plasma sputtering), which exhibits a high response value (100 ppm-4.16) and quick response-recovery time (1.5 s/38 s). The enhancement of gas-sensing performance benefits from a high Co3+/Co2+ ratio, which provides strong CO-selective adsorption and oxidation capabilities. Therefore, the interfacial oxidation reaction reaches equilibrium rapidly. This work provides a straightforward and controllable modification approach and enhances the understanding of how oxygen vacancies and Co3+ affect Co3O4 gas sensors, which promotes the design and development of high-performance cobalt-based gas sensors.

Combined Speed and Distance Control for Optimized Vehicle Platooning

Abstract This paper presents a novel approach to vehicle platooning using hybrid formation-regulation control, aiming to enhance the operation of Connected and Autonomous Vehicles (CAVs). By integrating advanced control algorithms with precise positioning and synchronization tools, our methodology enables CAVs to autonomously navigate while maintaining minimal inter-vehicle distances, thus optimizing convoy synchronization. The proposed system consists of two main controllers: a speed consensus controller to synchronize vehicle speeds and a following distance controller to ensure safety. Our hybrid control approach combines these controllers dynamically based on real-time vehicle spacing, employing exponential functions to smooth the transition between control modes, thereby preventing abrupt changes in vehicle behavior. This method not only increases energy efficiency and traffic throughput but also significantly reduces the likelihood of accidents caused by sudden braking, contributing to decreased fuel consumption and enhanced road safety. Our work not only advances the technology of vehicle platooning but also promises broader implications for the overall transportation ecosystem.

Performance Comparison and Analysis of Four- and Six-Switch Inverter Controls of BLDC Motor Employing Deep Learning

Robust and effective control of brushless dc (BLDC) motors is paramount in modern-day motion control. The BLDC motor is known for its high speed, high torque, small size, low noise, and equally low maintenance requirements compared to the brushed DC motor. Nowadays, it can be found in the areas of robotics, aerospace, military, and industrial machines, among others. In this paper, two inverter topologies, the threephase six-switch driver circuit (TPSSDC) and the three-phase four-switch driver circuit (TPFSDC), are used to drive and control the speed of the BLDC motor. For the control technique, however, a fitting neural network from the deep learning (DL) toolbox is employed to train and improve the speed performance of the motor. Both TPSSDC and TPFSDC are simulated and tested in MATLAB Simulink, and the resultant output is analyzed graphically and analytically. Graphical observation shows that the TPSSDC control approach is superior in terms of reference tracking and has less ripple, and better rise and settling times when compared to the TPFSDC control approach, however, the TPFDC is considered for its low cost and simple circuitry. Numerically, the TPSSDC also outperforms at 1000 rpm with a 1.685 ms rise time and a 1.420 ms settling time compared to the TPFSDC, which rises at 6.526 ms and settles at 5.237 ms. At 3000 rpm motor speed, the TPSSDC is better, having a rise time of 5.815 ms and settling time of 4.048 ms, when compared to the TPFSDC, which rises at 11.277 ms and settles at 10.067 ms.

Observer‐based adaptive neural networks optimal control for spacecraft proximity maneuver with state constraints

AbstractThis article proposes an adaptive neural network (NN) optimal control approach for autonomous relative motion control of non‐cooperative spacecraft in proximity. The proposed method aims to minimize fuel consumption under various challenges including model uncertainty, state constraints, external disturbances, and input saturation. To account for uncertain parameters of non‐cooperative target and external disturbances, we start by designing a NN disturbance observer. Subsequently, a novel optimal control index function is presented. An adaptive NN based on the actor‐critic (A‐C) framework and backstepping theory is then utilized to approximate the solution of Hamilton–Jacobi–Bellman (HJB) equation and obtain an optimal control law. The Lyapunov framework is leveraged to establish the stability of the closed‐loop control system. Finally, numerical simulations are conducted to assess the feasibility and effectiveness of the proposed control scheme in comparison with an existing approach.

Calculation Method for Particle Self-Regulation Servo Based on Discrete Element Method

Particle Flow Code, as noncontinuous media calculation software, has found extensive applications in geotechnical engineering research. To simulate real physical processes, the commonly utilized servo-computing methods involve adjusting the boundaries to modify the model’s stress state. However, this approach alters the model’s initial boundaries, thereby compromising computational accuracy. Addressing this issue, this paper introduces a particle self-regulation servo-computing method. This method controls the internal particle self-adjustment and completes the servo through error analysis. On the basis of the error analysis of the average stress within the particle system and the servo stress during the iterative process, the method automatically calculates the change in particle size within the system, achieving rapid convergence to servo stress tolerance after finite number of iterations. Validation through uniaxial compression tests and complex slope cases indicates that this particle self-regulation servo method yields an error of less than 5% compared with conventional rigid servo methods. That is, it accurately achieves numerical simulation state control without altering the outer contours of the boundary model. The proposed computational method is applicable to servo calculations for irregular models in two or three dimensions, providing a viable approach for stress control in models under complex conditions.

Vaping habits and respiratory symptoms using a smartphone app platform

BackgroundWidespread use of e-cigarette (EC) or vaping products causes respiratory disorders including the nationwide outbreak of e-cigarette or vaping product use-associated lung injury (EVALI) in 2019. Chronic adverse health effects are now being reported as well. To address this important public health issue, an innovative approach of epidemic control and epidemiologic study is required. We aimed to assess the association between short-term and long-term use of EC products and respiratory health in adults using smartphone app data.MethodsA population-based, repeated measures, longitudinal smartphone app study that performed 8-day survey participation over 60 days for each participant from August 2020 to March 2021, including 306 participants aged 21 years and older in the US. The participants were asked to complete the respiratory health questionnaire daily, weekly, and monthly on their smartphone app. We analyzed the association between vaping habits and respiratory health using generalized linear mixed models (GLMMs).ResultsEC use in the previous 7 days was associated with frequent cough (OR: 5.15, 95% CI: 2.18, 12.21), chronic cough (OR: 3.92, 95% CI: 1.62, 9.45), frequent phlegm (OR: 3.99, 95% CI: 1.44, 11.10), chronic phlegm (OR: 3.55, 95% CI: 1.41, 8.96), episodes of cough and phlegm (OR: 4.68, 95% CI: 1.94, 11.28), mMRC grade 3–4 dyspnea (OR: 3.32, 95% CI: 1.35 to 8.13), chest cold (OR: 3.07, 95% CI: 1.29, 7.33), eye irritation (OR: 2.94, 95% CI: 1.34, 6.47) and nose irritation (OR : 2.02, 95% CI: 0.95, 4.30). Relatively long-term effects of the past 90 days EC use was associated with an increased risk of wheeze (OR: 3.04, 95% CI: 1.31, 7.03), wheeze attack (OR: 2.78, 95% CI: 1.07, 7.24), mMRC grade 3–4 dyspnea (OR: 2.54, 9% CI: 1.05 to 6.18), eye irritation (OR: 3.16, 95% CI: 1.49, 6.68), and eye irritation during the past month (OR: 3.50, 95% CI: 1.52, 8.04).ConclusionsIn this smartphone app-based repeated measures study, short-term and relatively long-term use of EC increased the risk of respiratory symptoms.

Finite-time adaptive NN dynamic surface control for nonstrict nonlinear FOSs subject to input dead-zone and full-states constraints

This article focuses on a kind of nonstrict nonlinear fractional-order systems (FOSs) suffering from state constraints and dead-zone input. Meanwhile, a finite-time adaptive dynamic surface control (DSC) approach based on backstepping technology and approximation principle of radial basis function neural network (RBFNN) is developed. To overcome the problem of inherent computational complexity, a fractional-order filter is applied to approach the virtual controller and its fractional-order derivative in each step of the backstepping procedure. The barrier Lyapunov function (BLF) is employed to handle the state constraints, and finite-time stability criteria on the basis of fractional-order Lyapunov method are introduced to prove the finite-time convergence of the tracking error into a small region around the origin. It is shown that all the solutions of the closed-loop system are bounded, while the state constraints are satisfied within a predetermined finite time. Finally, two examples are provided to demonstrate the effectiveness of the presented control scheme.

Optimal and robust control methodologies for 4DOF active suspension systems: A comparative study with uncertainty considerations

AbstractDrawing from recent developments in the field, this article explores advanced control methodologies for active suspension systems with the aim of enhancing ride comfort and vehicle handling. The study systematically and comprehensively implements, simulates, and compares five control methods: Proportional‐integral‐derivative (PID), linear quadratic regulator (LQR), , , and synthesis in the context of half‐vehicle active suspension systems. By using a detailed system model that includes parameter uncertainties and performance weights, analysis, and simulations are conducted to evaluate the performance of each control approach. The results provide valuable insights into the strengths and limitations of these methods, offering a comprehensive comparative analysis. Notably, the study reveals that control may not ensure stability for all possible combinations within a broad range of uncertainties, indicating the need for careful consideration in its application. The results and simulations thoroughly evaluate and compare the performance of each control strategy across various output responses, contributing to the advancement of more effective and reliable active suspension systems.

Composite sliding mode control for cyber‐physical systems with multi‐source disturbances and false data injection attack

AbstractThis paper investigates the sliding mode control problem for cyber‐physical systems subject to multi‐source disturbances and actuator false data injection attacks simultaneously. Firstly, a series of extended state observers are designed to estimate the unknown multi‐source disturbances. For the actuator false data injection attacks, a sliding mode observer is designed to online estimate the values of attacks. Then, by introducing the disturbance and attack estimations, a dynamic sliding manifold and a composite sliding mode controller are constructed. Under the proposed approach, the unknown disturbances and false data injection attacks can be timely estimated and compensated, which can improve the disturbance rejection ability and guarantee security of the cyber‐physical system. Lyapunov theory is utilized to prove the stability of the closed‐loop system. Finally, simulations of both the numerical example and application to a power converter system demonstrate the effectiveness and superiority of the proposed composite sliding mode control approach.

Optimized sliding mode control for improved frequency response in an Islanded microgrid system

ABSTRACT This paper presents an enhanced Sliding Mode Control (SMC) approach in an Islanded Microgrid (IMG) system for regulating its frequency. The system encounters unpredictable disturbances arising from internal and external factors such as fluctuations in generation and demand, parameter variations, time delay, and many more. These factors challenge the frequency control during load fluctuations. To overcome these challenges, an Integral Sliding Mode-Load Frequency Control (ISM-LFC) as a robust control strategy employing integral sliding surface is proposed to regulate the system frequency. Particle Swarm Optimization (PSO) technique is used for optimal performance of ISM-LFC by meticulously determining the control variable parameters. A Simulink model of the IMG system in MATLAB is developed for conducting a comprehensive simulation analysis under diverse operational scenarios. The result outcomes affirm the effectiveness of the proposed controller using Integral sliding surface and modified saturation function-based control law for improved frequency response. Furthermore, comparative analysis with other alternative control strategies validates the improved performance of optimised ISM-LFC for frequency stabilisation.

Combining biological control approaches for managing insect crop pests in the field can generate interactive effects

Combining biological control approaches for managing insect crop pests in the field can generate interactive effects

Mathematical modelling and control approach for sustainable ecosystems in mitigating the impact of pollutants on aquatic species in rivers

This paper focuses on the urgent issue of minimising the impact of pollutants on aquatic life in river ecosystems. Our innovative approach involves the integration of mathematical modelling and strategic control methods to counteract the negative consequences of industrial and agricultural activities. The model, developed in a one-dimensional context, captures the complex dynamics of species population and pollutant concentration. Using an optimisation framework, we strive to achieve a harmonious balance that limits pollution, enhances species diversity and optimises control expenditure. Ultimately, we seek to harmonise industrial progress with ecological vitality, promoting the sustainability of river ecosystems for generations to come.

Development of a defined medium for the heterotrophic cultivation of Metallosphaera sedula

The heterotrophic cultivation of extremophilic archaea still heavily relies on complex media. However, complex media are associated with unknown composition, high batch-to-batch variability, potential inhibiting and interfering components, as well as regulatory challenges, hampering advancements of extremophilic archaea in genetic engineering and bioprocessing. For Metallosphaera sedula, a widely studied organism for biomining and bioremediation and a potential production host for archaeal ether lipids, efforts to find defined cultivation conditions have still been unsuccessful. This study describes the development of a novel chemically defined growth medium for M. sedula. Initial experiments with commonly used complex casein-derived media sources deciphered Casamino Acids as the most suitable foundation for further development. The imitation of the amino acid composition of Casamino Acids in basal Brock medium delivered the first chemically defined medium. We could further simplify the medium to 5 amino acids based on the respective specific substrate uptake rates. This first defined cultivation medium for M. sedula allows advanced genetic engineering and more controlled bioprocess development approaches for this highly interesting archaeon.

Does biodiversity affect Olive fly populations? Evidence from different understorey treatments

The agricultural industry is intensifying production methods to increase crop yields. Olive cultivation, the prevalent permanent crop in Europe and the Mediterranean area, involves intense practices with heavy agrochemical use. This significantly impacts agroecosystem biodiversity and its ecosystem services. In this study, we explore how biodiversity influences the adult olive fly (Bactrocera oleae (Rossi)) population in Lesvos Island, Greece, under different understorey management practices in olive groves. Our findings show that increased plant and arthropod abundance and diversity negatively affect the olive fly. The results suggest that maintaining undisturbed plant cover enhances olive grove biodiversity, ecosystem services, and biological control of the olive fly. Moreover, this practice is in line with Integrated Pest Management principles and Conservation Biological Control approach.

Leader-Following Connectivity Preservation and Collision Avoidance Control for Multiple Spacecraft with Bounded Actuation

This paper investigates the distributed formation control of a group of leader-following spacecraft with bounded actuation and limited communication ranges. In particular, connectivity-preserving and collision-avoidance controllers are proposed for the leader with constant or time-varying velocity, respectively. The communication graph between the spacecraft is modeled via a distance-induced proximity graph. By designing a virtual proxy for each spacecraft, the spacecraft–proxy couplings address the actuator saturation constraints. The inter-proxy dynamics incorporated with a bounded artificial potential function fulfill the coordination of all proxies. In addition, the bounded potential function can simultaneously tackle connectivity preservation and collision avoidance problems. The distributed formation controllers are proposed for multiple spacecraft with constant or time-varying velocities relative to the leader. A sliding mode control approach and the proxies’ dynamics are used in the design of a distributed cooperative controller for spacecraft to address the cooperative problem between the followers and the leader. Numerical simulations confirm the effectiveness of the anti-saturation distributed connectivity preservation controller.

Effect of weekly fever-screening and treatment and monthly RDT testing and treatment on the infectious reservoir of malaria parasites in Burkina Faso: a cluster-randomised trial

The majority of Plasmodium spp infections in endemic countries are asymptomatic and a source of onward transmission to mosquitoes. We aimed to examine whether Plasmodium falciparum transmission and malaria burden could be reduced by improving early detection and treatment of infections with active screening approaches. In this 18-month cluster randomised study in Sapone, Burkina Faso, households were enrolled and randomly assigned (1:1:1) to one of three groups: group 1 (control) received standard of care only, group 2 received active weekly, at home, fever screening by a community health worker regardless of symptoms, participants with a fever received a rapid diagnostic test (RDT) and treatment if RDT positive, and group 3 received active weekly fever screening (as in group 2) plus a monthly RDT regardless of symptoms, and treatment if RDT positive. Eligible households had a minimum of threeeligible residents, one in each age group (<5years, 5-15years, and >15years). The primary outcome was parasite prevalence by quantitative PCR (qPCR) in the end-of-study cross-sectional survey. Secondary outcomes included parasite and gametocyte prevalence and density in all three end-of-season cross-sectional surveys, incidence of infection, and the transmissibility of infections to mosquitoes. This trial was registered at ClinicalTrials.gov (NCT03705624) and is completed. A total of 906individuals from 181households were enrolled during two phases, and participated in the study. 412individuals were enrolled between Aug 9and 17, 2018, and participated in phase 1and 494individuals were enrolled between Jan 10and 31, 2019, in phase 2. In the end-of-study cross-sectional survey (conducted between Jan13and21,2020), Pfalciparum prevalence by qPCR was significantly lower in group 3 (29·26%; 79of 270), but not in group 2 (45·66%; 121of 265), when compared with group 1 (48·72%; 133of 273; risk ratio 0·65 [95% CI 0·52-0·81]; p=0·0001). Total parasite and gametocyte prevalence and density were also significantly lower in group3in all surveys. The largest differences were seen at the end of the dry season, with gametocyte prevalence 78·4% and predicted transmission potential 98·2% lower in group 3than in group1. Active monthly RDT testing and treatment can reduce parasite carriage and the infectious reservoir of Pfalciparum to less than 2% when used during the dry season. This insight might inform approaches for malaria control and elimination. Bill & Melinda Gates Foundation, European Research Council, and The Netherlands Organization for ScientificResearch.

Practical prescribed‐time tracking control of unknown nonlinear systems: A low‐complexity approach

AbstractThis article is concerned with the trajectory tracking control problem for the nonlinear systems in the sense of the predefined settling time and accuracy. In contrast with the existing works, we focus on the cases where the system dynamics, its bounding functions, the unmatched disturbances, and the time‐varying parameters are totally unknown; the derivatives of the desired trajectory are not required to be available. They significantly challenge the identification and/or approximation‐based control solutions. To overcome this obstacle, a novel robust prescribed performance control approach via state feedback is put forward in this article. It not only ensures the natural satisfaction of the specific initial condition but also realizes a full‐time performance specification for trajectory tracking. Furthermore, for the case of unmeasured state variables, an output‐feedback control approach is further derived by adopting an input‐driven filter and conducting trivial changes on the design procedure. Moreover, both approaches exhibit significant simplicity, without the needs for parameter identification, function approximation, disturbance estimation, derivative calculation, or command filtering. Three simulation studies are conducted to clarify and verify the above theoretical findings.