Synergetic Control Research Articles

Terminal Synergetic Control with the Dragonfly Algorithm for Zoonotic Visceral Leishmaniasis Eradication

Visceral Leishmaniasis (VL) is a prevalent vector-borne disease that affects both human and animal populations in subtropical and tropical regions, contributing to a substantial mortality rate. Establishing efficient control policies is crucial to eradicating the VL epidemic. The VL epidemic system, containing reservoirs, vectors, and human populations, can be accurately modeled through differential equations. Managing the VL epidemic under multiple control policies can be considered a high-order nonlinear feedback control challenge. This study explores the application of Terminal Synergetic Control (TSC) to eradicate Zoonotic Visceral Leishmaniasis (ZVL). Notably, Synergetic Control (SC) is one of the suitable feedback control methods for manipulating high-order nonlinear systems, providing practical control inputs because of their chattering-free behavior. Additionally, the convergence properties of the control system can be enhanced through terminal attraction. Optimization of control parameters within the system is achieved through the integration of control mechanisms by the Dragonfly Algorithm (DA). The results demonstrate that the multiple control policies synthesized by the TSC method effectively regulate subpopulations in alignment with the specified control objectives. Furthermore, the enhanced convergence rate achieved by the TSC method, in comparison to the SC method, serves as evidence of TSC's effectiveness in guiding the dynamics of ZVL epidemic eradication. This research underscores the potential of the TSC method, utilizing optimal control parameters provided by the DA, to achieve targeted outcomes with improved convergence properties.

Magnetic-Electrical Synergetic Control of Non-Volatile States in Bilayer Graphene-CrOCl Heterostructures.

Anti-ferromagnetic insulator chromium oxychloride (CrOCl) has shown peculiar charge transfer and correlation-enhanced emerging properties when interfaced with other van der Waals conductive channels. However, the influence of its spin states to the channel material remains largely unknown. Here, this issue is addressed by directly measuring the density of states in bilayer graphene (BLG) interfaced with CrOCl via a high-precision capacitance measurement technique and a surprising hysteretic behavior in the charging states of the heterostructure is observed. Such hysteretic behavior depends only on the history of magnetization, but not on the history of electrical gating; it can also be turned off electrically, providing a synergetic control of these non-volatile states. First-principles calculations attribute this observation to magnetic field-controlled charge transfer between BLG and CrOCl during the phase transition of CrOCl from antiferromagnetic (AFM) to ferrimagnetic-like (FiM) states. This magnetic-electrical synergetic control mechanism broadens the scope of proximity effects and opens new possibilities for the design of advanced 2D heterostructures and devices.

Transient behavior of pumped storage-wind hybrid power system under grid-connected operation condition

The large-scale grid connection of renewable energy represented by wind power threatens the safe and stable operation of electric system. The vigorous development pumped storage power station (PSPS) is a global consensus to support the grid-connected of renewable energy. This paper investigates the transient behavior of pumped storage-wind (PSW) hybrid power system under grid-connected operation condition (GCOC). Firstly, a model of PSW hybrid power system under GCOC is constructed. The stable domain is determined according to Hopf bifurcation theory. The influence of system parameters on the stability of PSW hybrid power system under GCOC is analyzed. A synergetic control strategy is designed to improve the dynamic performance of the system. Then, the mechanism of multi-time-scale dynamic response is revealed. Finally, the transient behavior of PSPS under different application scenarios and the interaction between PSPS and wind power station (WPS) are studied. The results show that the stability of PSW hybrid power system under GCOC can be judged by stable domain. The designed synergetic control strategy can improve the dynamic performance of the system. The dynamic response is composed of three oscillations with different frequencies, namely, mass oscillation at low frequency, water hammer oscillation at medium frequency, and electrical oscillation at high frequency. The principal oscillation is caused by water hammer. The interaction between PSPS and WPS has a significant effect on the transient behavior. By adjusting the interaction between PSPS and WPS, the system can absorb more wind power while ensuring safe and stable operation, which can increase profits and avoid unnecessary operation oscillations. The analytical methods and results presented in this paper are of great significance for improving the ability of power grid to accept renewable energy.

Quadrotor attitude control with a modified fixed‐time synergetic controller: A geometric analysis and experimental validation

AbstractThis article proposes a novel modified fixed‐time synergetic control (MFTSC) approach to address the quadrotor control problem in the presence of external disturbances. In contrast to previous fixed‐time synergetic control (FTSC) methods, the proposed approach employs an aggregate macrovariable expression with independent fractional powers. This expression expands the set of real numbers that the parameters of the fractional power can take, leading to a significantly higher rate of convergence toward optimal control parameters (more than 28‐fold), as demonstrated through geometric analysis. The stability of the proposed control system is established, and numerical simulations and experimental validation are conducted using a quadrotor test bench to corroborate the theoretical results.

Synergetic control analysis of CO2 and air pollutants in the automobile manufacturing industry in Guangdong-Hong Kong-Macao Greater Bay area: The supply chain perspective

The pollution reduction and carbon-cutting measures of Guangdong-Hong Kong-Macao Greater Bay Area (GBA) set a benchmark for sustainable development in China's urban agglomerations. While the automobile manufacturing industry significantly boosts the GBA's economic growth, its extensive cross-regional and cross-sector supply chains pose challenges for CO2 and pollution emission control. Analyzing emissions characteristics and transfer paths can clarify the GBA's role and guide targeted reduction measures. According to the multi-region input-output (MRIO) model and structural path analysis (SPA), this study clarifies that the automobile manufacturing industry in Guangdong, Hong Kong and Macao causes more than 72% of the CO2 and air pollutant (SO2, NOX, PM10) spillover to other regions, where the energy-resource-dominant upstream regions of Hebei, Shandong, and Henan emit high levels of CO2 and air pollutants, according for 19% of indirect supply chain emissions; the energy sector, non-metals sector, and metals sector are the key upstream, according for 59% of indirect supply chain emissions. Furthermore, our study identifies the Beijing-Tianjin-Hebei and neighboring regions, parts of the western region, and the GBA region and the metal products industry, automobile manufacturing industry, and water, electricity, and gas supply industry sector as the core area and key sector with significant synergistic effects on CO2 and air pollutant emissions. Therefore, implementing emission reduction measures in the identified core areas and sectors will contribute to the achievement of synergistic enhancement. These findings can inform decision-makers to promote sustainable development in the region. Furthermore, the research perspective based on the industrial chain offers new insights into defining regional responsibility for CO2 emissions and enhancing regional cooperation.

China's progress in synergetic governance of climate change and multiple environmental issues.

Advancing the synergetic control of climate change and environmental crisis is crucial for achieving global sustainable development goals. This study evaluates synergetic governance levels over climate change and four environmental issues at the provincial level in China from 2009 to 2020. Our findings reveal significant progress in China's coordinated efforts to mitigate carbon emissions, reduce air pollutants, and conserve water resources. However, there remains room for improvement in managing solid waste and protecting ecological systems and overall progress in synergetic governance has slowed since 2015. Employing a random forest model, we identify socio-economic factors with great influence on synergetic climate change and environmental governance, such as energy intensity, service sector development, electronic equipment manufacturing, and transportation. Additionally, we reveal nonlinear relationships between some factors and performance of environmental subsystems, including both plateau effects (e.g. output in the smelting of ferrous metals) and U-shaped patterns (e.g. output in the manufacturing of metal products), possibly attributed to constraints in end-of-pipe treatment capacities and complexities in supply chain networks. Furthermore, through hierarchical clustering analysis, we classify provinces into four groups and provide tailored recommendations for policymakers to enhance synergetic governance levels in their respective regions. The framework established in this study also serves as a valuable reference for countries seeking to develop practical and context-specific solutions to mitigate climate and environmental risks.

Synergetic control of multi‐level interface structure of basalt fibers by plasma and chemical functionalization to enhance the mechanical, thermal and interfacial performances of PBZ composites

AbstractThe composites of polybenzoxazine (PBZ) containing functionalized plasma treatment basalt fibers (fP‐BFs) were fabricated through in‐situ polymerization‐mixing technique. fP‐BFs is an effective reinforcement material that can improve the mechanical, thermal, and interfacial properties of composites. Surface activation of fP‐BFs can be enhanced through plasma modification, which improves the interaction between fP‐BFs and 3‐aminopropyltriethoxysilane. A systematic study on fP‐BFs/PBZ composite showed that a processing power of 300 W, a processing time of 5 min, and a fiber content of 9% can achieve good comprehensive mechanical properties. Thermogravimetric analysis results showed that fP‐BFs‐7/PBZ has the highest thermal stability, and its carbon residue rate, decomposition temperature and thermal decomposition activation energy are 36.80%, 452.2 °C and 133.56 kJ/mol, respectively. The dynamic mechanical analysis experiment showed that the addition of fP‐BFs improved the Tg of the composites. Among them, fP‐BFs‐5/PBZ showed the highest Tg, reaching 233.2 °C.Highlights Plasma treatment produced multi‐level structure of basalt fibers (fP‐BFs). Polybenzoxazine (PBZ)/fP‐BFs composites showed excellent performance. Interfacial bonding mechanism between fP‐BFs and PBZ was elucidated. Interfacial interactions between BFs and PBZ contributed to property enhancement. This work provided a green fabrication strategy of PBZ composites.

A longitudinal study of volatile organic compounds from cooking under ventilation and purification intervention: Health risk assessment and odor nuisance control

Cooking oil fumes (COFs) expose occupants to hazardous air pollutants and nuisance odors, hence the real controlling effects of different intervention methods deserve to be explored. This longitudinal study conducted year-round field measurements in 10 apartments to explore the synergistic effects of dual ventilation and purification interventions on the exposure level, odor intensity, and health risk control of gaseous organic compounds during cooking. Gas chromatography-mass spectrometry (GC‒MS) and high performance liquid chromatography (HPLC) were used for quantification of volatile organic compounds (VOCs) and carbonyls. A total of 59 VOCs were detected during cooking, and the average ΣVOC concentrations in summer, the transition seasons, and winter were 483.16 μg/m3, 233.97 μg/m3, and 282.82 μg/m3, respectively, and the proportion of aldehydes was approximately 50 %. The small temperature differences between the indoors and outdoors led to a 24 % reduction in the effective air changes per hour (ACH) in the summer compared with that in other seasons. The average estimated carcinogenic risks of formaldehyde, acetaldehyde and benzene were 9.20 × 10−5, 1.11 × 10−5, and 6.05 × 10−6, respectively, for daily cooking conditions. It is difficult to guarantee a healthy cooking environment by mechanical ventilation alone. The inhalation carcinogenic risk of these 3 hazardous VOCs was reduced by approximately 130.9 % under air purification intervention but was still greater than 1E-6. The noncarcinogenic risk of acrolein under the different intervention modes ranged from 69.8 to 84.9. Moreover, acetaldehyde and hexanal were found to be the key odorants in kitchen. When the effective exhaust air rate was greater than 12 m3/min with air purifier in operation, the average inhalation health risk was 1.05–1.78 times that before cooking, and more than half of the users would not smell obvious odors during the cooking process. This study quantifies the effectiveness of the synergetic control strategy of independent purification modules combine with kitchen mechanical ventilation, with a view to implementing a healthy & comfortable living environment.

Nonlinear MPPT techniques to control hybrid power systems

In recent years, grid-connected multifunctional photovoltaic (PV) systems have proven to be highly efficient. This system integrates PV panels with a DC–DC boost converter (DC–DC–BC) and the electrical distribution grid (DEG). Linking the PV to the AC-DEG is accomplished through a three-level multifunctional voltage source inverter (MVSI). The DC–DC–BC component in this study is engineered to perform maximum power point tracking (MPPT) irrespective of normal or abnormal conditions. The conventional MPPT technique poses several challenges and constraints on system usage. Hence, the suggestion is to adopt synergetic control (SC) and sliding mode control (SMC) to enhance the MPPT technique's performance within the proposed system framework. Moreover, predictive direct power control is applied to the MVSI-based shunt active power filter, utilizing a phase-locked loop technique to achieve multiple objectives: minimizing energy fluctuations, injecting active power, correcting power factors, compensating reactive power, and mitigating harmonic currents. To implement the proposed system, the MATLAB is used for this purpose, with several tests used to study the behavior of the controls proposed in this work. Numerical results indicate significant reductions in active and reactive power fluctuations, with estimated rates of 38.46% and 15.30%, respectively, compared to traditional strategies. Moreover, the total harmonic distortion (THD) of the source current after filtering is reduced by 31.88% under solar irradiation of G = 1000 Wm2. Before filtering, the THD of current experiences a reduction estimated at 97.65%. These findings underscore the superior performance of the proposed control technique across all evaluated aspects.

Experimental assessment of fuzzy-tree adaptive synergetic control law for DC/DC buck converter

Experimental assessment of fuzzy-tree adaptive synergetic control law for DC/DC buck converter

Deep deterministic policy gradient for adaptive power system stabilization and voltage regulation

This paper focuses on the challenges posed by the time-variable and nonlinear nature of energy systems. In this systems set points fluctuate due to load variations, generator losses, and disturbances such as short circuit faults. Maintaining power system stability and effectively damping low-frequency oscillations are crucial objectives. To enhance damping and dynamic stability in modern systems power system stabilizers (PSSs) are typically employed. These facilities generate auxiliary control signals for the generator excitation system, diminishing oscillations. In this study, by involving a deep deterministic policy gradient (DDPG) based on a synergetic control approach to the excitation system of synchronous generators, a novel approach to achieving fast and adaptive stability improvement and voltage regulation is suggested. The presented technique incorporates an intelligent synergetic PSS that effectively stabilizes the voltage response of a single machine connected to an infinite bus power system. To leverage its adaptive capability in controller parameter adjustments, an auxiliary deep DDPG algorithm with an Actor-Critic architecture is designed. The suggested procedure offers a promising avenue for effectively handling electromechanical oscillations and achieving improved voltage regulation and transient stability in power systems.

Fixed-time Synergetic Control for Synchronization of Fractional-order Chaotic Systems

In this paper, a fixed-time synergetic control is proposed for the synchronization of fractional-order chaotic systems. It is similar to the sliding mode approach but without chattering and achieves exact convergence of the macro-variable. Synergetic control is a robust approach that does not require linearization and is suitable for real-time implementation since it does not require a discontinuous term in its control law. The Lyapunov framework is used to ensure the convergence of the controlled system. Computer simulations are performed to illustrate the effectiveness of the proposed method.

Automated Shape Correction for Wood Composites in Continuous Pressing

The effective and comprehensive utilization of forest resources has become the theme of the global “dual-carbon strategy”. Forestry restructured wood is a kind of wood-based panel made of wood-based fiber composite material by high-temperature and high-pressure restructuring–molding, and has become an important material in the field of construction, furniture manufacturing, as well as derivative processing for its excellent physical and mechanical properties, decorative properties, and processing performance. Taking Medium Density Fiberboard (MDF) as the recombinant material as the research object, an event-triggered synergetic control mechanism based on interventional three-way decision making is proposed for the viscoelastic multi-field coupling-distributed agile control of the “fixed thickness section” in the MDF continuous flat-pressing process, where some typical quality control problems of complex plate shape deviations including thickness, slope, depression, and bump tend to occur. Firstly, the idea of constructing the industrial event information of continuous hot pressing based on information granulation is proposed, and the information granulation model of the viscoelastic plate shape process mechanism is established by combining the multi-field coupling effect. Secondly, an FMEA-based cyber granular method for diagnosing and controlling the plate thickness diagnosis and control failure information expression of continuous flat pressing is proposed for the problems of plate thickness control failure and plate thickness deviation defect elimination that are prone to occur in the continuous flat-pressing process. The precise control of the plate thickness in the production process is realized based on event-triggered control to achieve the intelligent identification and processing of the various types of faults. The application test is conducted in the international mainstream production line of a certain type of continuous hot-pressing equipment for the production of 18 mm plate thickness; the synergistic effect is basically synchronized after 3 s, the control accuracy reaches 30%, and the average value of the internal bond strength is 1.40, which ensures the integrity of the slab. Practical tests show that the method in the actual production is feasible and effective, with detection and control accuracy of up to ±0.05 mm, indicating that in the production of E0- and E1-level products, the rate of superior products can reach more than 95%.

Nonlinear modelling and design of synergetic controllers for single penstock multi-machine hydropower system

The existence of a shared pipeline in a multi-machine system can lead to hydraulic coupling effects between units. It increases the difficulty of controlling hydroelectric units and affects the stability of the power system. This paper refines the model of the hydroelectric generator unit and builds a nonlinear model of a hydro-generator unit with the single penstock multi-machine system. The synergetic control theory was introduced, and the governor and excitation system controllers were designed separately. A joint synergistic controller is obtained by analyzing the two systems' synergistic factors and controlled characteristics. This controller realizes the joint control of the excitation and governor system. The simulation selected a proportion-integral-derivative (PID) controller with optimized parameters, synergistic governor controller (SEC), and synergistic excitation controller (SGC) for comparison to verify the effectiveness of the proposed method. The results indicate that the proposed control method exhibits competent control effects in the single penstock multi-machine system. It can reduce the impact of hydraulic coupling, shorten the adjusting time, and ensure the fast and stable operation of the system. In addition, the values of system time parameters and synergetic control parameters are analyzed separately to provide a reference for achieving optimal control.

Adaptive synergetic control for electronic throttle valve system

AbstractThis study has developed adaptive synergetic control (ASC) algorithm to control the angular position of moving plate in the electronic throttle valve (ETV) system. This control approach is inspired by synergetic control theory. The adaptive controller has addressed the problem of variation in systems parameters. The control design includes two elements: the control law and adaptive law. The adaptive law is developed based on Lyupunov stability analysis of the controlled system, and it is responsible for estimating the potential uncertainties in the system. The effectiveness of the proposed adaptive synergetic control has been verified by numerical simulation using MATLAB/Simulink. The results showed that the ASC algorithm could give good tracking performance in the presence of uncertainty perturbations. In addition, a comparison study has been made to compare the tracking performance of ASC and that based on conventional synergetic control (CSC) for the ETV system. The simulated results showed that the performance of ASC outperforms that based on CSC. Moreover, the results showed that the estimation errors between the actual and estimated uncertainties are bounded and there is no drift in the developed adaptive law of ASC.

Optimal synergetic control using chaotic dragon fly-based MPPT with cascaded ANFIS method for ultrafast electric vehicle charging by hybrid RES systems

Optimal synergetic control using chaotic dragon fly-based MPPT with cascaded ANFIS method for ultrafast electric vehicle charging by hybrid RES systems

Terminal Synergetic Control for Plate Heat Exchanger

Terminal synergetic control (TSC) is proposed as a control strategy for the temperature management of a plate heat exchanger. The controller is designed by incorporating a selected macro variable with a time-varying sliding surface. The primary objective is to maintain precise control over the outlet temperature of the cold water. To assess the convergence characteristics of the newly proposed TSC approach, the simulation results achieved using TSC featuring a time-varying macro variable are compared to those obtained from the conventional synergetic control (SC) method. With an appropriate macro variable, the simulation results indicate a notable improvement in the convergence rate provided by our designed TSC method, compared to the conventional one. The desirable property of control input, the chattering-free condition, achieved by both TSC and SC approaches emphasizes the advantage of the synergetic control-based techniques over the conventional sliding mode controller. In conclusion, synergetic control-based techniques offer superior potential solutions for nonlinear feedback control problems.

Evaluation of control techniques for quadcopter UAV attitude tracking

ABSTRACT This paper evaluates the performance of six controllers used for the attitude tracking of the quadcopter. The evaluation is done by testing the tracking performance and robustness of each controller with respect to unknown dynamics, disturbances, gain variations, and noise. These controllers include the well-known Proportional-Integral-Derivative (PID) controller to establish a baseline, the Linear Active Disturbance Rejection Controller (LADRC), the first-order Sliding Mode Controller (SMC), the second-order Super-Twisting SMC (STSMC), the Backstepping Controller (BSC), and synergetic controller. To ensure a fair and systematic evaluation, the parameters of each control method were optimised using a Particle Swarm Optimizer (PSO), incorporating a penalty term to maintain realistic control signals while minimising error. The paper details the control techniques used and describes the optimisation process. The results suggest the superiority of LADRC over the other controllers. In the conclusion section, the paper presents several prospective strategies aimed at enhancing the discussed control techniques.

High potential in synergizing the reduction of dissolved organic carbon concentration and carbon dioxide emissions for submerged-vegetation-covered river networks

Various technologies and projects have been explored and developed for the synergetic control of environmental pollution and carbon emissions in aquatic ecosystems. Planting submerged vegetation in shallow waters was also expected to achieve this purpose. However, the magnitude and mechanism of carbon dioxide (CO2) emission affected by submerged vegetation is not clear enough in complex aquatic ecosystems. This study investigated the influences of submerged plants on CO2 emission, ecosystem metabolism features, and microbial community traits based on observations in river networks on the Changjiang River Delta. The results showed that CO2 emission from planted waters accounted for 73% of unplanted waters. Meanwhile, planted waters had higher dissolved organic carbon removal capacity in overlying water and higher potential of carbon sequestration in sediment at the same time. These distinctions between the two habitats were attributed to (1) improved CO2 and bicarbonate consumption in water columns via enhancing photosynthesis and (2) inhibited CO2 production by reconstructing the benthic microbial community. Additional eco-advantages were found in planted sediments, such as a high potential of methane oxidation and xenobiotics biodegradation and a low risk of becoming black and odorous. In brief, submerged vegetation is beneficial in promoting pollution removal and carbon retention synchronously. This study advances our understanding of the feedback between aquatic metabolism and CO2 emission.

Adaptive neural synergetic heading control for USVs with unknown dynamics and disturbances

This paper delves into the challenge of heading control for unmanned surface vehicles (USVs) in conditions with unknown dynamics and environmental disturbances. Adaptive neural synergetic controllers are introduced for the purpose of effectively steering the USV, ensuring precise heading control to track and maintain the desired angle, even in the presence of environmental disturbances such as sea winds and waves. Firstly, different forms of macro variables and evaluation constraints are introduced to design the synergetic controllers. Then, to estimate the unknown dynamics and environmental disturbances, a single input single output RBF neural network is developed. Besides, to ensure tracking at the desired angle, an adaptive neural synergetic law is derived from the Lyapunov stability theorem. Finally, the simulation results compare the control effect of heading controllers with different macro variables and evaluation constraints and verify the effectiveness of the proposed control strategy. The feasibility of the adaptive neural synergetic controller is verified through the USV experiment.