Control Approach Research Articles

Identification and functional analysis of gut dsRNases in the beet armyworm Spodoptera exigua

RNA interference (RNAi)-based products have the potential to significantly contribute to insect pest control. However, RNAi efficiency varies widely among different insect orders, particularly in Lepidoptera, where it is often low. One key factor affecting RNAi efficiency is the presence of double-stranded ribonuclease (dsRNase) in the digestive tract, which can degrade dsRNA prior to uptake by gut cells. In this study, four dsRNases were identified in the beet armyworm, Spdoptera exigua, of which two were highly expressed gut dsRNases, SedsRNase1 and SedsRNase2. To assess their effect on dsRNA degradation activity via the oral route, CRISPR/Cas9-based gene editing was employed to knock out these gut dsRNases. The results indicate that all mutant strains, including SeKO1 (knockout SedsRNase1), SeKO2 (knockout SedsRNase2), and SeKO1KO2 (knockout SedsRNase1 and SedsRNase2), showed significantly decreased dsRNA degradation activity, particularly in the SeKO1KO2 mutant strain, where the weakest degradation occurred in both the gut and whole body. Additionally, we noticed that the lack of gut SedsRNases led to a slight extended developmental period and reduced reproductive capacity in S. exigua. Collectively, these findings deepen our understanding of gut SedsRNases and how they can impact the biology of the beet armyworm and can support the exploration dsRNA-based approaches for pest control.

Phenotypic and Genetic Characteristics of Carbapenemase-Producing Enterobacterales Isolates at Okayama University Hospital.

Spread of carbapenemase-producing Enterobacterales (CPE) is an ongoing public health issue worldwide, including in Japan. In this study, we investigated the phenotypic and genetic characteristics of CPE isolates at Okayama University Hospital over the 5 years (2013-2018) prior to the outbreak of the 2019 coronavirus pandemic. Of 24 carbapenem-resistant Enterobacterales isolated during the study period, we identified 8 CPE isolates harboring blaIMP-1 (5 isolates) and blaIMP-6 genes (3 isolates). Bacterial species and carbapenem susceptibility patterns exhibited diversity. Minimum inhibitory concentrations (MICs) of meropenem were generally higher than those of imipenem and biapenem. Results of pulsed-field gel electrophoresis demonstrated that neither clonal nor plasmid-mediated outbreaks of blaIMP-harboring CPE isolates have developed at our hospital. One Klebsiella oxytoca isolate showed a high MIC (128 μg/mL) of meropenem, which could be explained by the high plasmid copy number. Subsequent analysis of this isolate may elucidate the intricacies of carbapenem resistance profiles among CPE isolates. Collectively, our findings underscore the necessity for ongoing genetic surveillance of CPE, complemented by tailored approaches for infection prevention and control.

The rising tide of tuberculosis in Pakistan: Factors, impact, and multi-faceted approaches for prevention and control.

Tuberculosis (TB) remains a major public health concern in Pakistan, which is ranked fifth among high-burden TB nations worldwide. The growing frequency of drug-resistant TB strains, particularly multidrug-resistant TB (MDR-TB), creates new obstacles. Socioeconomic factors, a lack of awareness, and inadequate healthcare infrastructure all contribute to the spread of the disease. This study investigates the mechanisms contributing to the growth in tuberculosis cases in Pakistan, the implications for public health, and multifaceted approaches to prevention and control. A comprehensive literature study was undertaken, including an analysis of peer-reviewed articles, World Health Organization (WHO) data, and government sources, to identify factors driving tuberculosis prevalence, control issues, and disease-fighting tactics.Result: Several factors like Poverty, overcrowding, malnutrition, stigma, and restricted access to healthcare services are all factors contributing to an increase in tuberculosis incidence in Pakistan. The prevalence of MDR-TB, along with a lack of an integrated healthcare response, complicates efforts to contain the disease's spread. Tuberculosis has a profound social, mental, and financial impact on individuals and communities. Public health efforts, such as the National Tuberculosis Control Program (NTP) and international partnerships, have been created to eradicate tuberculosis, although considerable hurdles persist. This study investigates the mechanisms contributing to the growth in tuberculosis cases in Pakistan, the implications for public health, and multifaceted approaches to prevention and control.

التحكم في سرعة المحركات الحثية باستخدام التحكم العددي ذو الحلقة المغلقة

In this study, the scalar control approach is applied to the control of induction motors three phase. The approach of scalar control is based on the maintaining a constant ratio between voltage-to-frequency (V/f) ratio, both theoretical and simulation-based analyses were performed to examine the performance of the method, which was seen to be successfully applied in speed control for induction machine, making it suitable for various industrial application. Simulations are performed to change the speed by changing the input voltage and changing the input voltage frequency. Finally, the performance of the V/f controlled three-phase induction motor is investigated. Simulations are performed using different speed references and the results are presented.The results show that the V/f controlled three-phase induction motor has good speed tracking performance. The simulations are performed in MATLAB/SIMULING environment. Keywords: Induction motor, speed control, scalar control, closed loop, (V/f) control

A compliant helical structure to amplify inertia for nonlinear vibration absorption

The vibration absorption is a passive approach for vibration control by attaching a secondary vibration system to realize the energy transfer and dissipation. To generate a sufficient inertial force, vibration absorbers need to introduce large additional mass, and thus the engineering applications are limited. In this study, a novel compliant structure is proposed with the inertial amplified through a helical movement, and the structure is adopted for nonlinear vibration absorption. The dynamic equations of the absorber are established based on the Lagrange equation, characterizing the nonlinear characteristics arising from the large deformation of the structure and the nonlinear kinetic relationship between the translation and the rotation. Amplitude-frequency responses of the absorber under different excitations are solved using the harmonic balance method and the arc-length continuation method. A rotation-inertial dominant absorber (RIDA) and a translation-inertial dominant absorber (TIDA) are fabricated with the same helical structure while different mass distributions and experiments are performed to validate the nonlinear characteristics and vibration absorption effects. It is observed that both RIDA and TIDA demonstrate effective vibration absorption performances., RIDA introduces smaller additional mass than TIDA. The proposed helical structure absorbers exhibit combined nonlinearities of softening stiffness and displacement-dependent inertia and damping, demonstrating resonance shifting and jump phenomena. With an increasing excitation amplitude, the vibration absorption efficiency decreases and then increases.

A Passivity-Based Approach for Variable Stiffness Control With Dynamical Systems

A Passivity-Based Approach for Variable Stiffness Control With Dynamical Systems

The Study on Controllable Preparation and Release Performance of Thermo‐Responsive Self‐Bursting PNIPAM Microcapsules

AbstractA straightforward microfluidic approach has been developed to fabricate the monodisperse thermo‐responsive self‐bursting poly(N‐isopropylacrylamide) (PNIPAM) microcapsules for the rapid on‐demand release of liposoluble drugs. The PNIPAM microcapsules possess excellent structural integrity with a dense shell and spacious cavity, providing ample space for encapsulating liposoluble matters. The swollen hydrogel shells effectively prevent drugs leakage and contamination below the volume phase transition temperature (VPTT), while the shrunken hydrogel shells enable drugs to release from microcapsules above the VPTT. The microcapsules demonstrate rapid thermo‐responsiveness, with drug release occurring within 4–6 minutes and subsequent swelling taking place within 2–3 minutes. The PNIPAM microcapsules exhibit a reversible and repetitive swelling/shrinking response to temperature changes. The thermo‐responsive self‐bursting PNIPAM microcapsules exhibit great potential as microcarriers for encapsulating, storing, and rapidly releasing liposoluble substances such as drugs, fluorescent dyes, corrosion inhibitors, and other chemical ingredients. The simple, controllable and reproducible microfluidic approach presented here provides valuable guidance for the design and fabrication of monodisperse PNIPAM microcapsules.

Anticorrosive two-dimensional heterostructured nanocoatings self-assembled on steel with multiple desired merits

In this study, an economic and controllable Marangoni self-assembly approach is designed to prepare the heterostructured nanocoatings (8–28 nm) consisting of alternately stacked mosaic nanosheets of hexagonal boron nitride (h-BN) and graphene. The resulting 2D nanocoatings exhibit a combination of advantageous properties, such as prevention of interfacial reactions, robust interfacial binding, a labyrinthine barrier effect, inhibition of galvanic corrosion, and alleviation of internal stress. The protective property of graphene/h-BN heterostructured nanocoatings is studied through potentiodynamic polarization curves and electrochemical impedance spectroscopy, with the theoretical support of first-principles calculations. The corrosion current density of ≈28 nm-thick graphene/h-BN multilayer coated stainless steel is 1.82 × 10−8 A cm−2, which decreases by an order of magnitude compared to that of an uncoated one, meanwhile, the corrosion potential increases from −0.192 to 0.023 V (increase: ≈0.215 V). The enhancement of anticorrosion performance of heterostructured nanocoatings can be attributed to the labyrinth barrier effect associated with highly ordered horizontal arrangement, effective coverage of metal substrates by mosaic multilayers, and suppressed galvanic corrosion effect by insulating BNNS monolayers. This study can shed much light on the effective solution of many stubborn issues confronted by the development of anticorrosive 2D nanocoatings.

The relationship between bone mineral density, vitamin D level, and sleep quality in postmenopausal women with osteoporosis: a relation-seeker type study.

This study was conducted to determine the relationship between bone mineral density, vitamin D level, and sleep quality in female patients with osteoporosis. This descriptive correlational study included a total of 318 women diagnosed with osteoporosis. The data were collected using a patient identification form, including items for the plasma vitamin D level and bone mineral density score obtained by the dual-energy X-ray absorptiometry method, and the Pittsburgh Sleep Quality Index. The mean age of the women was 56.49±5.68 years, and their femoral neck T mean score, an indicator of bone mineral density, was -2.94±0.31. Only 6.3% of the women had adequate vitamin D levels. In addition, according to their Pittsburgh Sleep Quality Index scores, 85.8% of the women had poor sleep quality. In the study, no significant difference was found between the women's bone mineral densities and vitamin D levels according to sleep quality (p>0.05). However, there was a weak negative correlation between the duration of osteoporosis, body mass index, and sleep quality (p<0.05). There was no association between the vitamin D level, bone mineral density, and sleep quality, but the duration of osteoporosis was negatively associated with sleep quality. Accordingly, it may be recommended to provide education and counseling to postmenopausal women diagnosed with osteoporosis on issues such as sunbathing, vitamin D and calcium preparation intake, weight control, and non-pharmacological treatment approaches by making necessary individual-specific plans to improve sleep quality.

Low-Complexity Tracking Control of Unknown Strict-Feedback Systems With Quantitative Performance Guarantees.

This article is concerned with the prescribed performance tracking control problem for the strict-feedback systems with unknown nonlinearities and unmatched disturbances. The challenge lies in the realization of a complete performance specification for trajectory tracking in the sense of quantitatively regulating the peak value, overshoot, settling time, and accuracy while ensuring that the initial condition holds naturally. To this end, an error transformation, equipped with a shifting function, is introduced and incorporated with a new-type barrier function. Then, a class of performance functions is exploited to quantify the settling times and steady-state bounds of the intermediate errors. Moreover, to improve the flexibility of formulating performance specifications for the tracking error, a pair of asymmetric performance boundaries are further designed. With their combination, a novel robust prescribed performance control (PPC) approach is proposed in this article. It not only achieves the quantitative performance guarantees but also preserves the unique simplicity of PPC, evading the needs for function approximation, parameter identification, disturbance estimation, derivative calculation, or command filtering. The above theoretical findings are confirmed via three simulation studies.

Gene Drive and Symbiont Technologies for Control of Mosquito-Borne Diseases.

Mosquito-borne diseases, such as dengue and malaria, pose a significant burden to global health. Current control strategies with insecticides are only moderately effective. Scalable solutions are needed to reduce the transmission risk of these diseases. Symbionts and genome engineering-based mosquito control strategies have been proposed to address these problems. Bacterial, fungal, and viral symbionts affect mosquito reproduction, reduce mosquito lifespan, and block pathogen transmission. Field tests of endosymbiont Wolbachia-based methods have yielded promising results, but there are hurdles to overcome due to the large-scale rearing and accurate sex sorting required for Wolbachia-based suppression approaches and the ecological impediments to Wolbachia invasion in replacement approaches. Genome engineering-based methods, in which mosquitoes are genetically altered for the modification or suppression of wild populations, offer an additional approach for control of mosquito-borne diseases. In particular, the use of gene drive alleles that bias inheritance in their favor is a potentially powerful approach. Several drives are frequency dependent, potentially giving them broadly similar population dynamics to Wolbachia. However, public acceptance and the behavior of released drives in natural mosquito populations remain challenges. We summarize the latest developments and discuss the knowledge gaps in both symbiont- and gene drive-based methods.

Iterative learning robust security predictive tracking control for small delay batch processes: Deception attacks on unreliable network channel

During the batch process, the need for security control is becoming increasingly urgent with the gradual penetration of network control technology. For small time delay batch processes subject to deception attacks, an iterative learning robust security predictive tracking control approach is developed. Reviewing previous studies for iterative learning control, the issue that the repetitive character of the batch process would mask the characteristics of deception attacks was not considered. Moreover, the gains of iterative learning control law are utilized offline, which makes large deviations for the system state as the operating time increases. This will lead to “excessive-input” conditions for control inputs, which means more consumption of energy and production resources. To address these challenges, we introduce robust security invariant sets to improve the robustness of the system by constraining the system state to be in a safe range. Also, the design of the iterative learning controller incorporates deception attack data for historical batches, which is continuously improved and optimized to withstand deception attacks. Meanwhile, by calculating stability conditions online, the real-time control law gain is obtained, which could make the control inputs adjusted online based on the real-time system’s dynamic characteristics, avoiding excessive inputs and improving the efficiency of energy and resource utilization. Additionally, the stability analysis proves that the system is input to state stability. Ultimately, simulation verifies the effectiveness and feasibility of the developed method.

A bi-level inter-phase coordinated control method for voltage regulation in unbalanced LV distribution networks using PV-battery energy storage systems

Photovoltaic systems coupled with battery energy storage (PV-BES) can help to minimize the effects of variability in PV generation including voltage problems in low voltage distribution grids (LVDNs). Therefore, a joint centralized-decentralized method consisting of two control levels based on sensitivity analysis is proposed in this paper, which employs the BES charging and discharging control in the first level and reactive power capability of inverters in the second control level. When the BES charging and discharging control is insufficient for voltage regulation, the second level of the proposed method is triggered. For full utilization of the BES capacity and to ensure adequate capacity for the following day's voltage regulation needs, an enhancement algorithm is applied to the voltage to active power sensitivity coefficients. All of the voltage sensitivity coefficients are calculated by a central controller using an offline procedure and sent to the PV-BES inverters to determine the amount of active and reactive power in real-time according to the measured local voltage. Taking into account the inter-phase voltage effects, a request for Var compensation signal flow with inter-phase coordination constraints is utilized to properly coordinate the inverters in reactive power control. The proposed method can efficiently regulate voltage by preventing over and under-voltage problems, improving the average total voltage deviation (TVD), reducing the total reactive power absorption and injection by the inverters, and avoiding reduction in PV generation. To evaluate the performance of the proposed control method, it is compared with the commercially available inverter voltage control techniques in an unbalanced residential test feeder. Moreover, a comparison is conducted between the proposed method and an adaptive decentralized control approach presented in the literature. Furthermore, a three-phase Volt-Var strategy, with and without the inter-phase coordination constraints, is simulated that indicates the necessity of the constraints for proper coordination.

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.

Vehicle platoon safety considering the vehicle cut-in: A coupled reinforcement learning and model predictive control approach

A longitudinal platoon control method based on Twin Delayed Deep Deterministic Policy Gradient (TD3) and Model Predictive Control (MPC) is proposed to solve the problems of low following efficiency and system instability in longitudinal platoon control. Firstly, Dynamic Bayesian Network (DBN) and Long Short-Term Memory (LSTM) network are introduced to identify the driving behavior of bystanders and derive the MPC objective constraint function containing three indicators of following, comfort and fuel consumption according to the platoon dynamics equation. Secondly, the system prediction model and cost function are introduced into the action-critic network of TD3 to solve the problem of no model training in the traditional TD3 algorithm and to speed up the training speed and accuracy of the network. On this basis, a Bellman equation is proposed to calculate the time-domain difference error and the expected loss function to solve the TD3 network overestimation problem. Finally, the joint simulation platform is built to simulate the platoon driving conditions and compare with the DDPG optimization algorithm and the traditional MPC algorithm respectively. The results show that the improved TD3-MPC algorithm satisfies the constraints and the spacing error is controlled within 0.3 m, and the vehicle speed changes more smoothly in the scenario of speed fluctuation in the front vehicle, and the ride comfort of the platoon is improved, and it has better robustness in the scenario of vehicle cut-in. The experimental results show that when the vehicle speeds are 20, 40, and 60 km/h, compared to MPC, the average spacing errors are reduced by 27.56%, 25.64%, and 28.04%, respectively, and compared to DDPG-MPC, the average spacing errors are reduced by 6.59%, 8.77%, and 7.86%, respectively.

Novel Controller Methodology for the Cessna Citation X Under Turbulence During Cruise

The design of a new control approach for the longitudinal motion of the Cessna Citation X during cruise is performed using a combination of sliding mode control (SMC) system, type 1 fuzzy logic system, and adaptive control system. This methodology is presented for 1) controlling the aircraft pitch rate and 2) stabilizing the aircraft speed during turbulence. The nonlinear model of the aircraft was generated using a simulation platform, which was designed based on flight data obtained from the highest Federal Aviation Administration–certified Level-D Research Aircraft Flight Simulator. The type 1 adaptive fuzzy logic system was implemented to approximate unknown functions for constructing the equivalent part of the SMC system that handled the effects of uncertainties and turbulence. The adaptation laws, derived from the Lyapunov theorem, were used to update the approximated functions in the control law at each flight condition and simulation iteration. Using the control systems combination, the pitch rate could follow the given reference signal, while the aircraft speed remained at a reference value with and without turbulence across the whole flight envelope. Results have shown that the proposed controllers satisfied tracking performance while generating smooth elevator deflection, both of which are important for real-aircraft applications.

A fast fixed-time backstepping control method for systems with mismatched disturbances

In this paper, a fast fixed-time backstepping control approach is developed for systems with mismatched disturbances. A novel fast fixed-time disturbance observer (FFTDO), which is convergent within fixed time regardless of initial conditions, is designed to efficiently estimate and compensate the disturbances. On the basis of FFTDO, a novel fast fixed-time backstepping control scheme is proposed, which can guarantee fast fixed-time convergence and high steady-state precision. In addition, a novel fixed-time filter is used to circumvent the problem of “explosion and complexity,” and to ensure overall fixed-time convergence. The fixed-time stability of the closed-loop system under the proposed controller is proved by the Lyapunov stability theory. The simulation results are carried out to confirm the feasibility and superiority of the proposed control strategy.

CLlight: Enhancing representation of multi-agent reinforcement learning with contrastive learning for cooperative traffic signal control

Multi-agent reinforcement learning has shown great potential for coordinating multi-intersection traffic signals due to its powerful adaptive capabilities, treating each intersection as an agent. However, in the real world, different intersections possess differentiating characteristics such as unique vehicle distributions and traffic patterns. Most existing methods directly add neighboring intersection states to local intersections and optimize the cooperative policy network based on synthesized global features. This indirect optimization approach makes it difficult to thoroughly explore the mutual interactions among different intersection agents, preventing agents from truly learning features with cooperative awareness. To resolve these challenges, we introduce contrastive learning as representation task to the multi-intersection traffic signal control approach named CLlight for two-stage policy network updating. In the first stage, we utilize policy-based or actor-critic-based reinforcement learning methods such as A2C, SAC, and PPO to train policy networks with certain representational capabilities. In the second stage, by extracting pre- and post-masked features and reconstructing the post-masked features, the agents are encouraged to learn the similarities and differences between different intersection policies, which in turn enhances the cooperative and individual representation capabilities of the policy network. To the best of our knowledge, this is the first application of contrastive learning in the field of traffic signal control. Experimental results demonstrate, compared to other state-of-the-art traffic signal control methods, superior average travel time and average waiting time performance under various scenarios, tested on synthetic and real-world datasets.

An Improved Predefined-Time Adaptive Neural Control Approach for Nonlinear Multiagent Systems

An Improved Predefined-Time Adaptive Neural Control Approach for Nonlinear Multiagent Systems

Distributed robust [formula omitted]asso-[formula omitted] based on [formula omitted]ash optimization for smart grid: Guaranteed robustness and stability

The integration of variable renewable energy supplies into smart grid energy management poses several obstacles to system operation. An efficient solution for resource management is essential to ensuring reliable operation. This research presents distributed robust Lasso-model predictive control (D − RLMPC) as a way to handle energy problems in a multi-layer and multi-time frame optimization method. The D − RLMPC is a hierarchical system that integrates a centralized supervisory management (SM) layer for long-term optimization with a distributed coordination management (CM) layer for short-term adaptation to high power fluctuations. The higher layer, known as the SM, is responsible for providing the grid operator with specific operating plans and offering guidance to the bottom layer, known as the CM. The CM is responsible for coordinating the interaction between the centralized optimization goals and the physical power system layer. Furthermore, a distributed extended Kalman filter (DEKF) is used to ascertain the inter-dependencies among subsystems. Next, an iterative approach based on Nash optimization is proposed to get the globally optimum solution of the whole system in a partly distributed manner. The simulation results demonstrate the effectiveness of the proposed control approach, which combines the advantages of centralized and distributed control to provide a comprehensive solution for the grid operating issue. To verify and assess the effectiveness of the suggested approach, the acquired outcomes are compared to those of the centralized robust, distributed robust, and distributedMPC approaches. The simulation findings confirm the practicality of using the suggested system to manage future smart grid assets.