Control Approach Research Articles

A Hybrid RBFNN-SPOA Technique for Multi-Source EV Power System with Single-Switch DC-DC Converter

With a single-switched DC-DC converter, a hybrid approach is proposed for a fast-charging (FC) dc to dc converter with the controller for an electric vehicle charging station (EVCS) that combines solar photovoltaic (PV), fuel cells (FC), and a battery energy storage system (BESS). The proposed hybrid technique integrates a radial-basis-function-neural-network (RBFNN) and a student-psychology-optimization-algorithm (SPOA); commonly known as the RBFNN-SPOA technique. The PV-FC hybrid electric vehicle systems, like controllers, electric vehicle, and the vehicle’s power source, are displayed. The proposed converter architectures have less voltage waveform changes, a low voltage stress on semiconductor power sources, and a high-voltage ratio of conversion. The proposed method is to use FC successfully at battery charge states and varied radiation levels. The FC in the controller of SPOA may change the inputs and outputs depending on the battery state of charge (SoC) and PV irradiation. Similarly, the needed input-torque for the motor is forecasted by the recalling recurrent neural network controller using several manually produced torque signals. The performance of the proposed technique is evaluated in MATLAB and is compared to ant colony optimization (ACO), crow optimization algorithm (COA), and fuzzy logic controller (FLC) approaches. According to the results, the efficiency of the proposed technique is 99.17%.

Fabrication of Fully Positively Charged Layer-by-Layer Polyelectrolyte Nanofilms with pH-Dependent Swelling Properties.

Nanofilms fabricated by layer-by-layer (LbL) assembly from polyelectrolytes (PEs) are important materials for various applications. However, PE films cannot retain the charges along the polymer chains during fabrication, resulting in a low charge density. In this study, the preparation of LbL nanofilms with preserved positive charges via a controllable and efficient approach was achieved. To fabricate fully positively charged (FPC) LbL nanofilms, a polycation, poly-l-lysine, was partially grafted with azide and alkyne groups. Through copper-catalyzed azide-alkyne cycloaddition and the LbL procedure, nanofilms were fabricated with all of the individual layers covalently bonded, improving the pH stability of the nanofilms. Because the resulting nanofilms had a high charge density with positive charges both inside and on the surface, they showed unique pH-dependent swelling properties and adsorption of negatively charged molecules compared with those of traditional polyelectrolyte LbL nanofilms. This kind of FPC nanofilm has great potential for use in sensors, diagnostics, and filter nanomaterials in the biomedical and environmental fields.

A bridge between influence models and control methods

Understanding how influence is seeded and spreads through social networks is an increasingly important study area. While there are many methods to identify seed nodes that are used to initialize a spread of influence, the idea of using methods for selecting driver nodes from the control field in the context of seed selection has not been explored yet. In this work, we present the first study of using control approaches as seed selection methods. We employ a Minimum Dominating Set to develop a candidate set of driver nodes. We propose methods based upon driver nodes (i.e. Driver-Random, Driver-Degree, Driver-Closeness, Driver-Betweenness, Driver-Degree-Closeness-Betweenness, Driver-Kempe, Driver-Ranked) for selecting seeds from this set. These methods make use of centrality measures to rank the driver nodes in terms of their potential as seed nodes. We compare proposed methods to existing approaches using the Linear Threshold model on both real and synthetic networks. Our experiment results show that the proposed methods consistently outperform the benchmarks. We conclude that using driver nodes as seeds in the influence spread results in faster and thus more effective spread than when applying traditional methods.

Splittable systems in biomedical applications.

Splittable systems have emerged as a powerful approach for the precise spatiotemporal control of biological processes. This concept relies on splitting a functional molecule into inactive fragments, which can be reassembled under specific conditions or stimuli to regain activity. Several binding pairs and orthogonal split fragments are introduced by fusing with other modalities to develop more complex and robust designs. One of the pillars of these splittable systems is modularity, which involves decoupling targeting, activation, and effector functions. Challenges, such as off-target effects and overactivation, can be addressed through precise control. This review provides an overview of the design principles, strategies, and applications of splittable systems across diverse fields including immunotherapy, gene editing, prodrug activation, biosensing, and synthetic biology.

A Method for Multi-AUV Cooperative Area Search in Unknown Environment Based on Reinforcement Learning

As an emerging direction of multi-agent collaborative control technology, multiple autonomous underwater vehicle (multi-AUV) cooperative area search technology has played an important role in civilian fields such as marine resource exploration and development, marine rescue, and marine scientific expeditions, as well as in military fields such as mine countermeasures and military underwater reconnaissance. At present, as we continue to explore the ocean, the environment in which AUVs perform search tasks is mostly unknown, with many uncertainties such as obstacles, which places high demands on the autonomous decision-making capabilities of AUVs. Moreover, considering the limited detection capability of a single AUV in underwater environments, while the area searched by the AUV is constantly expanding, a single AUV cannot obtain global state information in real time and can only make behavioral decisions based on local observation information, which adversely affects the coordination between AUVs and the search efficiency of multi-AUV systems. Therefore, in order to face increasingly challenging search tasks, we adopt multi-agent reinforcement learning (MARL) to study the problem of multi-AUV cooperative area search from the perspective of improving autonomous decision-making capabilities and collaboration between AUVs. First, we modeled the search task as a decentralized partial observation Markov decision process (Dec-POMDP) and established a search information map. Each AUV updates the information map based on sonar detection information and information fusion between AUVs, and makes real-time decisions based on this to better address the problem of insufficient observation information caused by the weak perception ability of AUVs in underwater environments. Secondly, we established a multi-AUV cooperative area search system (MACASS), which employs a search strategy based on multi-agent reinforcement learning. The system combines various AUVs into a unified entity using a distributed control approach. During the execution of search tasks, each AUV can make action decisions based on sonar detection information and information exchange among AUVs in the system, utilizing the MARL-based search strategy. As a result, AUVs possess enhanced autonomy in decision-making, enabling them to better handle challenges such as limited detection capabilities and insufficient observational information.

A new adaptive Perturb & Observe controller via robust approach for PV grid-connected

Given the importance of renewable energies, several countries are integrating these energies into their energy strategies, such as their connections to the grid, in particular photovoltaic energy. In this paper, a PV grid-connected system in a two-stage configuration is studied. In this configuration, an improvement to a control MPPT is proposed. To achieve this, we propose a novel concept for MPPT control that consists of generating an adaptive step size for P&O control that is based on sliding mode control in order to minimise ripple phenomena and chattering phenomena. The proposed control approach was then tested using MATLAB/Simulink simulations under varying irradiation conditions. We compared this approach to the conventional P&O method as well as the adaptive step size of P&O and hybrid P&O-sliding mode control. The results of the test indicate that the proposed control strategy significantly minimises the two phenomena and improves overall efficiency.

Model‐free event‐triggered distributed coordination control for dual‐arm reconfigurable manipulators with unknown object constraints

AbstractIn this paper, a model‐free event‐triggered distributed coordination control of dual‐arm reconfigurable manipulators is presented for handling unknown object task. Firstly, based on Newton‐Euler algorithm and kinematic analysis, the dynamic models of the dual‐arm manipulators and grasped object are established, respectively. According to the load distribution method, the motion‐induced force is effectively distributed to each arm. Then the dynamics of single‐arm manipulator for handling task is obtained. Secondly, the adaptive algorithm based on gradient model is proposed to estimate the position of object's center of mass (COM). The fusion state variable function is improved to achieve coordination control, reflecting the tracking performance of the position and internal force. For the modeless reconfigurable manipulator, the radial basis function neural network (RBFNN)‐based observer is utilized to approximate the uncertain dynamics. Further, the aperiodic model‐free distributed coordination controller is obtained through event‐triggered mechanism. Next, the uniformly ultimately bounded (UUB) stability of dual‐arm reconfigurable manipulators system is proved through Lyapunov stability theory. Finally, the experimental results verify that the proposed coordination control approach is valid.

Composite‐observer‐based asynchronous control for hidden Markov nonlinear systems with disturbances

SummaryIn this article, an asynchronous adaptive tracking control approach is presented for a type of hidden Markov jump nonlinear systems with external disturbances. In this joint jump process model, hidden Markov model signifies the dynamics of the actual system, whereas the signal emits from the detector symbolizes the transmitted information. This leads to the phenomenon of asynchronization between the modes of the system and that of the controller. Accordingly, an asynchronous observer is developed by using the mode information from the detector to develop an asynchronous control approach. The observer contains a disturbance estimation part, to compensate the unknown external inputs. Utilizing the backstepping scheme, a strict‐feedback asynchronous tracking controller is formulated, guaranteeing that all signals within the closed‐loop system are semi‐globally uniformly ultimately bounded in probability. Finally, the validity of the presented methodology is illustrated by means of a simulation example.

Nonlocal active sound control for composite regions

In the active sound control problem, additional sound sources, known as control sources, are implemented at the perimeter of a protected domain. The control sources can generate secondary sound inside the shielded domain, which attenuates incoming noise. This leads to an inverse source problem. Such a problem becomes much more complicated if some desired sound is generated inside the protected area. The algorithm, known as nonlocal active sound control, successfully tackles this problem due to the projection property of the nonlocal operators involved. With the application of nonlocal control, noise generated outside the shielded domain is attenuated while the internal component of sound remains unaffected. In the present paper, the approach of nonlocal active sound control is significantly modified to be applicable to composite domains. In the test cases, three different sound propagation patterns are realized such as sound shielded from peers, free propagation, and selective sound cancelation. Numerical simulation is carried out in both frequency and time domains for broadband regimes. The results show that, even with a relatively small number of sensors and control sources, significant noise attenuation can still be achieved for a predetermined communication pattern among individual subdomains.

Sinusoidal control strategy applied to continuous stirred‐tank reactors: Asymptotic and exponential convergence

AbstractThe main goal of this proposal is to present a class of nonlinear controllers for regulation and set point changes in continuous chemical reactors. The proposed control law has in its mathematical structure a proportional term of the regulation error to provide closed‐loop stability and a sinusoidal term, which can compensate for the nonlinearities of the plant. The closed‐loop stability of the plant is demonstrated via Lyapunov analysis, which reveals an asymptotic convergence of the control output to the required set points. Furthermore, the analysis of the regulation error's dynamic under the considered assumptions leads us to conclude that exponential stability is also reached. The controller is implemented via numerical experiments in two examples to generalize the applicability of the proposed approach by considering continuous stirred‐tank reactors models. The first case considers autocatalytic chemical oscillatory reactions that induce chaotic behaviour. For the second case, a process of acetone, butanol, and ethanol (ABE) fermentation through Clostridium acetobutylicum is considered. The proposed strategy shows an adequate performance because it can reach the required set point without long time settings and overshoot. A comparison with a smooth sliding‐mode and a standard proportional‐integral (PI) controller indicates the advantages of the proposed control approach.

Comparative evaluation of biological control programs and chemical pesticides for managing insect and mite pests in cucumber greenhouses: a sustainable approach for enhanced pest control and yield

BackgroundCucumber plants are susceptible to several economically damaging pests, including whiteflies, aphids, thrips and spider mites. This study aimed to evaluate the efficacy of two biological control programs, utilizing different releases of bio-agents, in comparison with chemical control method. The bio-agents used were the aphid parasitoid Aphelinus albipodus Hayat and Fatima (Hymenoptera: Aphelinidae), the green lacewing Chrysoperla carnea (Steph.) (Neuroptera: Chrysopidae) and the predatory mite Phytoseiulus persimilis Athias-Henriot (Acari: Phytoseiidae) in two release rates; low and high. Additionally, a chemical pesticides treatment was included for comparison in managing the pests in cucumber greenhouses during the winter seasons of 2022 and 2023, in Egypt. Abundances of whitefly, aphids, thrips and spider mites were recorded weekly throughout the study.ResultsThe aphid population in the greenhouse with high release rate (BIO 2) showed the highest reduction, with percentages of 84.55 and 89.88% in 2022 and 2023, respectively. Both greenhouse with low release rate (BIO 1) and BIO 2 exhibited significant reductions in the whitefly population, with proportions of 71.31 and 72.01% in 2022, and 82.05 and 85.94% in 2023, respectively. The thrips population also experienced notable reductions in both BIO 1 and BIO 2 greenhouses, with percentages of 72.08 and 75.71% in 2022, and 59.93 and 61.38% in 2023, respectively. However, the pesticide treatment demonstrated the lowest reduction in populations of aphids, whitefly and thrips in both seasons. Nevertheless, in all treatments in the two evaluated seasons, the high release rate of the predatory mite, P. persimilis (15 individuals/m2), proved to be highly effective in maintaining the mite populations below the economic threshold level. However, the population density of the two-spotted spider mite, Tetranychus urticae Koch. (Acari: Tetranychidae), increased in the pesticide-treated greenhouse, indicating the development of resistance to pesticides. Although the tested programs resulted in similar yields, the biological control approach offered the advantage of pesticide-free produce and reduced production costs.ConclusionFor pest management in cucumber growing in greenhouses during winter, it is recommended to use biological control agents at a low release rate at the early occurrence of pests. This approach can help minimize pest populations effectively.

Relay feedback identification and PI-PD control of asymmetrical heating and cooling processes

A common type of nonlinear system in the field of process industry is asymmetrical heating and cooling processes. These systems have two operating modes, heating and cooling, each with a particular dynamic feature. This study deals with identifying and controlling such processes. The relay feedback identification method based on the state-space approach, which results in exact estimates, is used in the identification procedure to achieve two first-order plus dead time (FOPDT) process models. Following process identification, two sets of PI-PD controller parameters are acquired in line with the user-defined gain and phase margin specifications, and the system is controlled using a gain-scheduled PI-PD control method. Some simulation examples are provided to demonstrate the use and profitability of the suggested identification and control approaches. Comparisons with a similar study are provided for both identification and control approaches to clearly demonstrate the benefits of the suggested procedures.

Efficient voltage regulation: An RW-ARO optimized cascaded controller approach

This work introduces novel advancements in automatic voltage regulator (AVR) control, addressing key challenges and delivering innovative contributions. The primary motivation lies in enhancing AVR performance to ensure stable and reliable voltage output. A crucial innovation in this work is the introduction of the random walk aided artificial rabbits optimizer (RW-ARO). This novel optimization strategy incorporates a random walk approach, enhancing the efficiency of AVR control schemes. The proposed cascaded RPIDD2-PI controller, fine-tuned using the RW-ARO, stands out as a pioneering approach in the AVR domain. It demonstrates superior stability, faster response times, enhanced robustness, and improved efficiency compared to existing methods. Comparative analyses with established controller approaches reaffirm the exceptional performance of the proposed method. The new approach results in shorter rise times, quicker settling times, and minimal overshoot, highlighting its effectiveness and speed in achieving desired system responses. Moreover, the novel approach attains higher phase and gain margins, showcasing its superior performance in the frequency domain. The disturbance rejection and harmonic analysis are performed in order to demonstrate the efficacy of the proposed approach for potential real-world applications. The latter analyses further cement the superior capability of the proposed approach for the automatic voltage regulation.

Complex vaccination strategies prevent the emergence of vaccine resistance.

Vaccination is the most effective tool to control infectious diseases. However, the evolution of vaccine resistance, exemplified by vaccine-resistance in SARS-CoV-2, remains a concern. Here, we model complex vaccination strategies against a pathogen with multiple epitopes - molecules targeted by the vaccine. We found that a vaccine targeting one epitope was ineffective in preventing vaccine escape. Vaccine resistance in highly infectious pathogens was prevented by the full-epitope vaccine, that is, one targeting all available epitopes, but only when the rate of pathogen evolution was low. Strikingly, a bet-hedging strategy of random administration of vaccines targeting different epitopes was the most effective in preventing vaccine resistance in pathogens with low rate of infection and high rate of evolution. Thus, complex vaccination strategies, when biologically feasible, may be preferable to the currently used single-vaccine approaches for long-term control of disease outbreaks, especially when applied to livestock with near 100% vaccination rates.

Antifungal efficacy of clove extract in fermented sausage production: A practical approach for microbial control and maintaining quality properties

Antifungal efficacy of clove extract in fermented sausage production: A practical approach for microbial control and maintaining quality properties

Antifungal efficacy of clove extract in fermented sausage production: A practical approach for microbial control and maintaining quality properties

Antifungal efficacy of clove extract in fermented sausage production: A practical approach for microbial control and maintaining quality properties

Prevalence of tobacco smoking and related factors in people aged 15 years and above in Beijing, 2014-2021

Objective: To evaluate the effect of the implementation of Beijing Smoking Control Regulation in 2015 on the smoking prevalence in people aged ≥15 years in Beijing during 2014-2021, and explore factors associated with tobacco use behavior in local population. Methods Using a pooled cross-sectional design, data from Beijing Adult Tobacco Survey in 2014, 2016, 2019 and 2021 (4 surveys) were combined into one dataset. The 4 surveys used same multistage cluster sampling procedure. After complex survey weighting, multiple logistic regression models were constructed to analyze factors influencing smoking status. Results: A total of 8 484, 9 372, 8 534 and 10 551 respondents were included in the surveys in 2014, 2016, 2019 and 2021, respectively. The smoking prevalence rate was 23.4%, 22.3%, 20.3% and 19.9%, respectively, in Beijing residents aged ≥15 years, exhibiting a linear declining trend (P=0.010). Factors associated with current smoking in men were age 25-44 years (OR=2.22, 95%CI: 1.68-2.95) and 45-64 years, (OR=2.64, 95%CI: 2.06-3.39), educational level of high school (OR=0.69, 95%CI: 0.49-0.95) and undergraduate and above (OR=0.46, 95%CI: 0.33-0.63), and awareness of smoking causing stroke (OR=0.71, 95%CI: 0.61-0.81), and awareness of smoking causing lung cancer (OR=0.53, 95%CI: 0.42-0.66), the differences were significant (all P<0.05). After controlling interfering factors, the current smoking prevalence in men in 2019 (OR=0.73, 95%CI: 0.63-0.87, P<0.001) and 2021 (OR=0.72, 95%CI: 0.61-0.88, P<0.001) were significantly lower than that in 2014. Factors associated with current smoking in women were living alone (OR=1.80, 95%CI: 1.33-2.44), educational level of undergraduate and above (OR=0.43, 95%CI: 0.27-0.69), other occupations except doctor and teacher (OR=8.54, 95%CI: 2.80-26.02) or being retired/unemployed (OR=9.39, 95%CI: 3.19-27.65), and awareness of smoking causing cardiovascular events (OR=0.58, 95%CI: 0.39-0.84), and awareness of smoking causing lung cancer (OR=0.54, 95%CI: 0.35-0.83), the differences were significant (all P<0.05). No significant change in smoking status in women was found in 4 surveys. Conclusions: The smoking prevalence rate in men in Beijing has declined since the implementation of Beijing Smoking Control Regulation 5 years, indicating the effectiveness of legislative approach in tobacco control. Socio-demographic factors and the awareness level of tobacco harm could influence smoking status. Future tobacco control programs should target the people with lower education level, young men, women living alone, and those with occupations other than teachers/doctors or the unemployed/retired and include more comprehensive health education.

Optimal fractional PI controller-based VSC-HVDC system with LCL filter design

For decades, high voltage direct current (HVDC) has been an essential means in designing smart microgrids. Though, a control approach for Voltage Source Converter (VSC)-based HVDC, like dampening oscillations, must be established for improved operational execution, as these oscillations can cause stability issues. Considering its versatility, the Fractional order Proportional Integral (FPI) controller is used in this study's control approach instead of the PI controller. With frequency domain analysis, comprehensive modelling and design of LCL filters for harmonic reduction to improve power quality are presented. The dynamic characteristics of VSC-HVDC are comprehensively presented based on dq axis synchronous frame of reference. The VSC-HVDC improved control outcome is validated by the result analysis using PI and FPI controller using ITLBO. It is found in both frequency and time-domain simulations and analysis that the AFPI-VSC-HVDC system is capable of effectively dampening oscillations to enhance the small-signal stability.

Analysis of speckle-beacon size impact on wavefront sensing and closed-loop control in deep turbulence conditions

The impact of the laser beacon size on the performance of an ideal phase-conjugation-type adaptive optics (AO) system is analyzed using wave-optics-based numerical simulation. The analysis includes wavefront aberration sensing and closed-loop control for laser beam propagation both in vacuum and in distributed (volume) atmospheric turbulence with the beacon beam scattering off a flat extended target with Lambertian surface roughness. For mitigation of the impact of target-induced speckle effects on the performance of AO systems, speckle-average wavefront sensing and control approaches are introduced and analyzed. The results demonstrate that proposed speckle-average phase conjugation control algorithms enable partial mitigation of turbulence-induced aberrations in presence of strong speckle modulations.

An alternative approach for the sediment control of in-channel stony debris flows with an application to the case study of Ru Secco Creek (Venetian Dolomites, Northeast Italy)

Controlling sediment to reduce debris-flow hazard is generally approached using retention basins that can be closed or have an outlet structure, generally an open check dam. They are usually placed in mild slope zones that allow minimal works for the excavation and the foundation of the outlet structure if present. Recently, it has been shown that the detention of sediments can also be achieved in the high-sloping reaches of debris-flow channels using deposition areas, basins that are open on the downstream side. In this work, we propose an approach for controlling the sediment volume transported by debris flows consisting of a cascade of deposition areas and retention basins. We also include a framework for planning, sizing, and checking the works. Two scenarios are considered, corresponding to the maximum values of the debris-flow peak discharge and volume, respectively. Moreover, the presence or absence of boulders is also considered. For this purpose, a method that evaluates the clogging of a single open check dam as a function of the coarse fraction of the sediment volume is simply extended to the case of multiple dams and implemented in a routing model. The proposed approach is applied along Ru Secco Creek in northeast Italy to defend a resort area and a village hit by a high-magnitude debris flow in 2015. After a careful survey and study, a solution with a combination of deposition areas and retention basins is planned and sized. The validity and performance of the proposed solution are analyzed using debris-flow modeling for two scenarios, considering both the absence and presence of boulders. Most of the sediment volume transported by debris flows is trapped, and a small solid discharge flows downstream of the works.