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In this paper, a novel two-stage epidemic model with a dynamic control strategy is proposed to describe the spread of Corona Virus Disease 2019 (COVID-19) in China. Combined with local epidemic control policies, an epidemic model with a traceability process is established. We aim to investigate the appropriate control strategies to minimize the control cost and ensure the normal operation of society under the premise of containing the epidemic. This work mainly includes: (i) propose the concept about the first and the second waves of COVID-19, as well as study the case data and regularity of four cities; (ii) derive the existence and stability of the equilibrium, the parameter sensitivity of the model, and the existence of the optimal control strategy; (iii) carry out the numerical simulation associated with the theoretical results and construct a dynamic control strategy and verify its feasibility.

To mitigate dangerous climate change effects, the 195 countries that signed the 2015 Paris Agreement agreed to “keep the increase in average global surface temperature below 2 °C and limit the increase to 1.5 °C” by reducing carbon emissions. One promising option for reducing carbon emissions is the deployment of carbon capture, utilization, and storage technologies (CCUS) to achieve climate goals. However, for large-scale deployment of underground carbon storage, it is essential to develop technically sound, safe, and cost-effective CO2 injection and well control strategies. This involves sophisticated balancing of various factors such as subsurface engineering policies, technical constraints, and economic trade-offs. Optimization techniques are the best tools to manage this complexity and ensure that CCUS projects are economically viable while maintaining safety and environmental standards. This work reviews thoroughly and critically carbon storage studies, along with the optimization of CO2 injection and well control strategies in saline aquifers. The result of this review provides the foundation for carbon storage by outlining the key subsurface policies and the application of these policies in carbon storage development plans. It also focusses on examining applied optimization techniques to develop CO2 injection and well control strategies in saline aquifers, providing insights for future work and commercial CCUS applications.

This article proposes a composite fault‐tolerant control strategy combining zero‐mode control and half‐wave reconfiguration to address single IGBT open‐circuit faults in cascaded H‐bridge converters. The composite strategy enables continuous operation without bypassing faulty modules by dynamically adjusting the working modes of faulty modules and reconstructing modulation waves for cascaded converters. The zero‐mode control strategy, as the core of this study, adopts a digital logic‐based architecture and utilizes the zero‐mode equivalence of the two operating modes of the H‐bridge module to dynamically switch modes according to the fault type. Through collaboration with the half‐wave reconfiguration control strategy, precise compensation for missing positive or negative voltage levels caused by faulty modules is achieved within a specific interval, ensuring that the cascaded converter can maintain output characteristics even under single IGBT open‐circuit faults and meet the requirements of grid‐connected operation. The maximum power control strategy dynamically adjusts the output power of faulty and healthy modules to minimize power deviations between them, thereby optimizing energy distribution efficiency and extending the lifespan of the battery energy storage system. Experimental results validate the effectiveness of the strategy in addressing single IGBT faults in cascaded energy converters. STEP1:Analyze the differential characteristics of four IGBT open‐circuit faults in the H‐bridge module. STEP2:Analyze the impact of different IGBT faults on PWM voltage within a switching cycle. STEP3:Establish a hierarchical and collaborative fault‐tolerant control system: The zero‐mode control strategy dynamically switches modes according to the fault type. The half‐wave reconfiguration control strategy compensates for missing positive or negative voltage levels caused by faulty modules. The maximum power control strategy dynamically adjusts the output power of the faulty and healthy modules to optimize energy distribution. STEP4:Experimental results validate the effectiveness of the proposed fault‐tolerant strategy in addressing single IGBT faults in cascaded energy converters.

Power electronic devices play an important role in energy conversion. Among the options, matrix converters, in combination with predictive control, represent a good alternative for the power conversion stage. Although several reviews have been undertaken on this topic, they have been conducted in a non-systematic manner, without indicating how the studies considered were chosen. This paper presents results from a systematic literature review on predictive control applied to matrix converters that included 142 primary papers, which were selected after applying a defined protocol with clear inclusion and exclusion criteria. The study provides a detailed classification of predictive control methods and strategies applied to different matrix converter topologies. Research findings require to be understood in combination to develop a common understanding of the topic and ensure that future research effort is based on solid premises. In light of this, this study identifies and characterizes different predictive control techniques and matrix converter topologies through systematic literature review. The results of the review indicate that interest in the area is increasing. A number of open questions in the field are discussed.

Concerns about climate change, air pollution, and the depletion of oil resources have prompted authorities to enforce increasingly strict rules in the automotive sector. There are several benefits to implementing fuel cell hybrid vehicles (FCHV) in the transportation sector, including the ability to assist in reducing greenhouse gas emissions by replacing fossil fuels with hydrogen as energy carriers. This paper examines different control strategies for optimizing the power split between the battery and PEM fuel cell in order to maximize the PEM fuel cell system efficiency and reduce fuel consumption. First, the vehicle and fuel cell system models are described. A forward approach is considered to model the vehicle dynamics, while a semi-empirical and quasi-static model is used for the PEM fuel cell. Then, different rule-based control strategies are analyzed with the aim of maximizing fuel cell system efficiency while ensuring a constant battery state of charge (SOC). The different methods are evaluated while the FCHV is performing both low-load and high-load drive cycles. The hydrogen consumption and the overall fuel cell system efficiency are considered for all testing conditions. The results highlight that in both low-load cycles and high-load cycles, the best control strategies achieve a fuel cell system efficiency equal or greater to 33%, while achieving a fuel consumption 30% less with respect to the baseline control strategy in low-load drive cycles.

In this study, a dual-loop control strategy is applied to a highly distributed architecture of photovoltaic/battery-based DC microgrid built through an interconnection of a cluster of multiple nanogrids. Typically, in these distributed architectures, resource sharing among the spatially distributed nanogrids is enabled via communication-based control methodologies, which adds cost and complexity to the overall system. Alternately, a communication-less and decentralised control methodology is proposed which utilises inner loop current control and outer loop voltage droop (V–I droop) control for the coordinated resource sharing among the distributed resources. The proposed control scheme adapts various modes based on the local measurements of bus voltage and battery state of charge, therefore, offers a distributed solution, omitting the need for centralised communication control. Various scenarios of power sharing among the contributing nanogrids are evaluated through the proposed multi-mode adaptive control. The efficacy of the proposed control scheme is validated through simulations on MATLAB/Simulink and laboratory scale hardware prototype. Results show that the proposed decentralised control strategy is capable to ensure stable and coordinated operation without any dedicated layer of communication among the dispersed generation/storage resources.

In this study, an observer based control strategy is proposed for load frequency control (LFC) scheme against cyber-attack uncertainties. Most of research work focused on detection scheme or delay estimation scheme in presence of cyber-attack vulnerabilities and paid less attention on design of counteractive robust control scheme for LFC problem. Thus, observer based control scheme is designed here and provides robust performance against unknown input attack uncertainty and communication time-delay attack uncertainty. The generalized extended state observer (GESO) is used not only for state and disturbance estimation but also for disturbance rejection of the system. The said observer ensures accurate estimation of the actual states leading to convergence of estimation error to zero. So, the observer based linear quadratic regulator (LQR) is used to regulate the closed-loop damping ratio against cyber-attack uncertainty. In addition to fast response in terms of settling time and reduced over/undershoots, the proposed control scheme satisfactorily compensates the cyber-attack uncertainties in power system cyber physical networks and also compared with existing traditional PI and PID controllers. The simulation results demonstrate the robustness in terms of stability and effectiveness in terms of system security with proposed controller when subjected to cyber-attack uncertainties and load disturbances.

Bean leaf beetles (BLBs) (Ootheca spp.) are important field insect pests of the common bean (Phaseolus vulgaris L.) in agricultural communities in Sub-Saharan Africa. A survey of 128 farmers was conducted in Arua, Hoima, Lira, and Lwengo districts in Uganda, where the common bean is a major food and income crop. This paper evaluated farmers’ knowledge, control strategies, and challenges in managing BLBs. Over 87% of the farmers in Arua and Lira could identify BLBs by local names, compared to less than 45% in Hoima and Lwengo. Less than 8% of the farmers in all districts were aware that BLBs oviposit, diapause, and then emerge from the soil. Many farmers (75%) in Lwengo perceived BLBs infestation as mild, 65.6% in Hoima thought it was moderate, and 78% and 56% in Arua and Lira respectively thought it was severe. The use of chemicals was popular in all districts and also perceived to be the most effective method for controlling BLBs. The reported obstacles to controlling BLBs were a lack of understanding of proper control methods, and the existence of fake insecticides on the market. We recommend that the Ministry of Agriculture, Animal Industry and Fisheries customizes the agricultural extension information packages to include BLBs and cost-effective control strategies for them.

This paper investigates the performance of various power control structures on a series power flow controller comprised as transformerless H-bridge inverter under different operating conditions. This power flow controller connects the main grid with the microgrid as it is seriesly attached with the distribution line. Three different control strategies are implemented to regulate the power flow at the interface point using the series power flow controller. The feasibility of the regulation approaches is verified by varying the modulation index and the reference DC-link voltage during different operation modes. Also, the performance of the control strategies is verified under load divergence condition during two different operation modes. The results showed the efficacy of the developed regulation methods in injecting series voltage at point of common coupling (PCC) either during the capacitive or the inductive operation mode. Also, the obtained results reveal the stability and reliability of the regulation methods and the microgrid operation when either the reference DC-link voltage or the modulation index are increased.

Dengue remains a major public health threat in tropical and subtropical regions. We develop a general human–vector SEIR–SEI optimal‐control framework that integrates four time‐dependent interventions: public awareness/behavioral protection, u1(t) ${{u}_1}( t )$ , enhanced clinical management u2(t) ${{u}_2}( t )$ , adulticide spraying u3(t) ${{u}_3}( t )$ , and larval‐source reduction/larvicide u4(t) ${{u}_4}( t )$ . The controls act by reducing effective human–vector contact, increasing human recovery, increasing adult mosquito mortality, and suppressing vector recruitment, respectively. The objective is to minimize a weighted sum of infectious burden in humans and vectors and the quadratic costs of implementation over a finite horizon, subject to epidemiological dynamics and standard control bounds 0 ≤ ui (t) ≤ 1. Using Pontryagin's Maximum Principle, we derive the necessary conditions for optimality and solve the resulting two‐point boundary value problem numerically. Numerical simulations conducted in MATLAB, calibrated with real data from Bangladesh, perform uncertainty and sensitivity analyses around the basic reproduction number and key transmission, and control parameters reveal that Strategy‐4, which includes public awareness, treatment, and insecticide spraying (u1(t)≠0,u2(t)≠0,u3(t)≠0,u4(t)=0 ${{u}_1}( t ) \\ne 0,\\ {{u}_2}( t ) \\ne 0,\\ {{u}_3}( t ) \\ne 0,{{u}_4}( t ) = 0$ ), is the most effective and cost‐efficient approach. This strategy reduces the time to disease elimination from over 100 days to approximately 74.7 days, achieving a 72.66% faster reduction than natural decay. The findings demonstrate that the proposed control strategies can significantly curb the progression of dengue and support targeted public health interventions to manage outbreaks effectively.