Stability Control Research Articles

Stability control and analysis of hydrogen production using a multi-terminal DC EV charging system with PV

In the shift towards sustainable energy, DC microgrids have emerged as efficient and reliable alternatives to traditional AC systems, particularly suited for low-voltage applications. The adoption of electric vehicles (EVs) in multi-terminal DC (MTDC) systems introduces challenges in maintaining voltage stability, particularly during master station failures. Our research introduces a decentralized control strategy with multi-mode switching to ensure stability under such conditions. We conduct a comprehensive stability analysis of MTDC systems heavily integrated with EVs, identifying the instability risks and proposing mitigation strategies. The effectiveness of our control approach is validated through simulation studies and a detailed state-space model. Additionally, we explore the integration of renewable energy sources and hydrogen production into MTDC systems for EV charging, which minimizes the need for a new power infrastructure and enhances renewable energy use. This integration optimally reduces renewable energy discard rates, thereby improving energy efficiency without compromising system performance. Our study provides practical insights and theoretical support for renewable energy-driven hydrogen production within DC microgrids. The proposed scheme's performance is validated through simulation studies using a state-space model.

A study on misfire detection by calculating crank angular velocity considering in-cylinder gas properties

Misfire detection using a new crank angular velocity calculation was studied for high efficiency and robust engine ignition performance and combustion stability control. An applying production was achieved by applying in-cylinder gas properties prediction and its correction to the misfire index and verifying it under various conditions. The relationship between the misfire index and torque fluctuation was consistent depending on the combustion control factors EGR, injection timing, pilot injection quantity change, and environmental change factors water temperature and intake gas temperature. On the other hand, it was found that the piston speed changes due to the in-cylinder pressure with respect to the intake pressure, and the crank angular speed needs to be corrected. Commonly used sensors for engine cooling water temperature, intake gas temperature, intake pressure, and engine speed were used as representative values for in-cylinder pressure, and the cooling loss was subtracted from the polytropic index and the reduction in specific heat ratio due to EGR was corrected. By building a new model that calculates the compression end pressure model from the polytropic index and adding corrections to the misfire index, we applied logic that can be calculated for each cycle to the ECU onboard. Conventionally, compression end pressure prediction requires calculations that take combustion conditions into account, which requires the number of sensors and their accuracy, and a long calculation time. However, in this study, Authors focused on the fact that the pressure at TDC during a misfire does not include ignition and combustion phenomena and expressed the necessary physical phenomena using the minimum sensor information. As a result of the above, a control structure at a level that can be applied to products was obtained.

Research on Vehicle Stability Control Based on a Union Disturbance Observer and Improved Adaptive Unscented Kalman Filter

This paper considers external disturbances imposed on vehicle systems. Based on a vehicle dynamics model of the vehicle with three degrees of freedom (3-DOFs), a union disturbance observer (UDO) composed of a nonlinear disturbance observer (NDO) and an extended state observer (ESO) was designed to obtain external disturbances and unmodeled items. Meanwhile, an improved adaptive unscented Kalman filter (iAUKF) with anti-disturbance and anti-noise properties is proposed, based on the UDO and the unscented Kalman filter (UKF) method, to evaluate the sideslip angle of vehicle systems. Finally, a vehicle yaw stability controller was designed based on UDO and the global fast terminal sliding mode control (GFTSMC) method. The results of co-simulation demonstrated that the proposed UDO was effectively able to observe external disturbances and unmodeled items. The proposed iAUKF, which considers external disturbances, not only achieves adaptive updating and adjustment of filtering parameters under different sensor noise intensities but can also resist external disturbances, improving the estimation accuracy and robustness of the UKF. In the anti-disturbance performance test, the maximum estimation error of the sideslip angle of the iAUKF under the three working conditions was less than 0.1°, 0.02°, and 0.5°, respectively. Based on the UDO and the GFTSMC, a vehicle yaw stability controller is described, which improves the accuracy of control and the robustness of the vehicle’s stability control system and greatly strengthens the driving safety of the vehicle.

Experimental and numerical study on the mechanical behavior of layered rock anchored by CRLD anchor cable

The study of the mechanical behavior of layered anchored rock is essential for addressing the stability control challenges of surrounding rock of the roadway in layered rock masses. This paper focuses on a novel constant resistance large deformation (CRLD) anchor cable and conducts a comparative study on the uniaxial compressive mechanical behavior of unanchored rock, conventional high-strength (HS) anchor cable, and CRLD anchor cable anchored rock under different bedding dip angles α (30°, 45°, 60°, 75°, and 90°). The strength characteristics, failure characteristics, and acoustic emission characteristics of various specimen types were analyzed with emphasis. The results indicate that with the increase of bedding dip angle, the elastic modulus, peak strength, and residual strength of all specimen types exhibit a trend of decreasing first and then increasing. Compared to unanchored and HS anchored rock, the values of various mechanical parameters for CRLD anchored rock show varying degrees of improvement. The failure modes of various specimen types under different bedding dip angles can be classified into five categories based on the characteristics of the crack distribution. Through comparison, it was found that the CRLD anchor cable can effectively restrict the occurrence of bedding shear failure within the anchored zone in layered rocks with smaller dip angles (30°, 45°). It also transforms the failure mode of layered rocks with larger dip angles (60°, 75°) from a single mode of bedding shear failure to a mixed mode of bedding-bedrock failure. However, under a bedding dip angle of 90°, the two types of anchored rocks exhibit similar failure forms. Comparing the acoustic emission characteristics of the two types of anchored rocks, it is observed that under different bedding dip angles, CRLD anchored rocks exhibit a more uniform distribution of acoustic emission counts, a smoother energy release process, and significantly lower peak count and cumulative energy values. Finally, a numerical model for layered CRLD anchored rocks was constructed based on the discrete element method. The reliability of the experimental results from the physical model in this study was verified by statistically analyzing the quantity evolution process and orientation distribution of microcracks in the numerical model.

Sampled-data static output feedback robust MPC for LPV systems with bounded disturbances

This paper investigates a sampled-data static output feedback robust model predictive control (MPC) approach for continuous-time linear parameter varying (LPV) systems with unknown system states and bounded disturbances. Between two successive sampling time instants, it is assumed that the controlled LPV systems evolve in continuous-time, and the control inputs are piecewise constant. The robust stability conditions and control input constraints on the closed-loop system are considered in the formulated robust MPC optimization. The constraints in the formulated robust MPC optimizations are formulated as linear matrix inequalities (LMIs) and solved as convex optimization. The designed sampled-data static output feedback robust MPC optimization has a simple structure and directly optimizes output feedback controller. Furthermore, the system state constraint sets are on-line updated over the sampling interval. The designed sampled-data static output feedback robust MPC approach has the property of recursive feasibility, and can guarantee robust stability of the controlled continuous-time LPV systems. A simulation example is given to illustrate the effectiveness of the approach.

Mixed Eucalyptus plantations enhance soil organic carbon accumulation and chemical stability through soil microbial community and multifunctionality

Forest conversion can impact soil organic carbon (SOC) fixation and ecosystem functions. The newly proposed “evenness of SOC chemical components” index can indicate the permanence of stored SOC during environmental disturbances. However, how the mixing of tree species impacts SOC accumulation and persistence and changes in soil microbial communities and multifunctionality remain unknown. Thus, we conducted a field experiment (11 years) of monospecific Eucalyptus urophylla × E. grandis plantation for evaluating the influences of the mixed planting of a non-nitrogen (N)-fixing tree, Castanopsis hystrix, and an N-fixing tree, Dalbergia odorifera, on SOC accumulation and chemical stability. Compared with pure plantations, mixed Eucalyptus plantations (particularly those mixed with D. odorifera) exhibited significantly increased SOC concentrations by 28.60–33.71 % and increased SOC chemical component evenness by 3.96–4.67 % (P < 0.05). We also found that the concentrations and chemical component evenness of SOC were strongly linked with litter quality, soil N, phosphorus and their availability, multifunctionality, microbial activity, carbon use efficiency (CUE), biomass, diversity, and network complexity. Furthermore, tree species mixing increased litter quality, soil nutrient availability, microbial biomass, activity, diversity, CUE, and network complexity. Soil microbial anabolism, community characteristics and multifunctionality influenced the SOC concentrations and SOC chemical components evenness. Specifically, microbial diversity enhanced the concentrations and chemical component evenness of SOC by increasing network complexity and soil multifunctionality. These findings revealed differential responses and mechanistic controls of SOC accumulation and chemical stability in different Eucalyptus planting patterns. Overall, mixed plantations, particularly those in which N-fixing species were introduced, effectively improved SOC accumulation and stabilization by positively altering soil quality and microbial properties, potentially representing a sustainable forestry management strategy to improve soil C benefits and multifunctionality in forest ecosystems.

Reliability in mass alert system for dam emergencies: Case study of Vale S/A

AbstractIn its iron ore operations, Vale, the largest mining company in Brazil and the fourth largest mining company in the world by market value, has 77 dams considered with high potential damage in case of a failure in the stability controls. This classification follows the criteria of the sector regulatory agency in Brazil and determines that, for this class, a mass alert system is necessary for the resident population and workers immediately downstream of the dam within a region preset by legislation, considering a simulated flood area. For Vale, the mass alert system for dam emergencies is part of a critical mitigating control for a business risk analysis considering the hypothetical dam break as an unwanted material event. Therefore, both the probability of failure on demand, spurious failure, and availability of the assets of this protection barrier are important elements for this purpose, as well as the emergency response plan and the evacuation simulation of flood areas, which are part of a risk management system that require continuous verification and continuous improvement. Currently, Vale has 375 sirens, and it is planned to reach 420 sirens by the end of 2024. The purpose of this article is to present how the safety concepts applied to these systems were developed, the good practices applied from this study, and the lessons learned from the dam emergency management arising from the break of the Brumadinho dam in 2019. The reliability analyses of the systems involved and the main contributors to the Safety Critical Unavailability are presented, as well as the results of the reduction in the maintenance time and increase in system availability.

Droop Frequency Limit Control and Its Parameter Optimization in VSC-HVDC Interconnected Power Grids

With the gradual emergence of trends such as the asynchronous interconnection of power grids and the increasing penetration of renewable energy, the issues of ultra-low-frequency oscillations and low-frequency stability in power grids have become more prominent, posing serious challenges to the safety and stability of systems. The voltage-source converter-based HVDC (VSC-HVDC) interconnection is an effective solution to the frequency stability problems faced by regional power grids. VSC-HVDC can participate in system frequency stability control through a frequency limit controller (FLC). This paper first analyses the basic principles of how VSC-HVDC participates in system frequency stability control. Then, in response to the frequency stability control requirements of the sending and receiving power systems, a droop FLC strategy is designed. Furthermore, a multi-objective optimization method for the parameters of the droop FLC is proposed. Finally, a large-scale electromagnetic transient simulation model of the VSC-HVDC interconnected power system is constructed to verify the effectiveness of the proposed droop FLC method.

Research on coal wall failure and stability control technology of large coal seams with a soft and thick seam

AbstractTo address the issues of coal rib instability and high occurrence of roof falls in high extraction height fully mechanized coal mining of soft coal seams, this study comprehensively employs theoretical analysis, numerical calculations, and field industrial experiments. By analyzing the distribution characteristics of coal rib displacement and deformation instability zones under different mechanical parameters of soft coal seams, the instability mechanism of coal ribs in high extraction height mining of thick and soft coal seams is revealed, and corresponding stability control techniques for high extraction height coal ribs and supports are developed. The study shows that the stability of coal ribs in high extraction height mining fields of soft and thick coal seams decreases as the values of mechanical parameters decrease. In other words, the smaller the cohesion and deformation parameters of the coal body, the more prone the coal rib is to roof falls. By utilizing advanced deep‐hole static water infusion technology, the frequency of roof falls in extremely soft high extraction height working faces is reduced by 80%, the average depth of roof falls is decreased by 35%, and the average length of roof falls is reduced by 50%. The stability of the coal ribs is effectively improved.

Self-Triggered Impulsive Control for Lyapunov Stability of Nonlinear Systems in Discrete Time.

This article studies Lyapunov stability for nonlinear systems based on discrete-time self-triggered impulsive control (STIC). With the help of comparison approach, some Lyapunov-based sufficient conditions guaranteeing nonZeno behavior and global asymptotic stability of nonlinear systems under STIC are derived. Different from the existing self-triggered mechanisms using implicit expressions to compute the next impulse instant, which may result in computational burden, we propose a novel discrete-time self-triggered mechanism (STM) by which the next impulse instant can be predicted directly by the information of the comparison system. Moreover, the resulting algorithm is easy to be implemented. It is shown that the designed STIC strategy can not only achieve a tradeoff between computational complexity, communication resource usage and control performance, but also has strong robustness and flexibility. Finally, an illustrative simulation is provided showing the effectiveness of the results.

A Study on the Steady and Dynamic Performance of Dry Gas Seals with Combined Superelliptical Grooves and Holes on the End Face

Background:: Enhancing the stability and leakage control of Dry Gas Seals (DGS) under high parameters has been a crucial research focus. The design of end-face groove structures and surface texture shapes has been an essential aspect of DGS studies aimed at improving performance. Objective:: The proposed end-face gas seal utilizes superelliptical grooves and holes to improve its performance, aiming to obtain a patent. The use of superelliptical curves allows for a more precise and efficient geometric representation, resulting in a better sealing effect. Methods:: A theoretical analysis model for the steady and dynamic behavior of the seal is established using the lubrication theory and perturbation methods. The study investigates the distribution patterns of gas film pressure on the sealing end-face and gas flow characteristics within the film. This approach provides a new perspective for understanding seal performance and offers a theoretical basis for optimizing seal design. Results:: The results indicate that the combined end-face structure with grooves and holes ensures good sealing stability and effectively enhances leakage control performance. By optimizing the design of the superelliptical groove and holes on the end face, the performance of DGS can be significantly improved. Conclusion:: Within the parameter range studied, better steady-state performance is achieved for θ=40~80°, v=1.3~1.4, u=1~2, β=0.6~0.7, and λ=1.0~1.5. In addition, better dynamic performance is observed for θ=80~120°, v=1.1~1.2, u=2~3, β=0.9~1.0, and λ=2.0~2.5.

Effects of mediolateral whole-body vibration during gait with additional cognitive load

Whole-body vibration (WBV) may increase musculoskeletal disorder risk among workers standing on vibrating surfaces for prolonged periods. Limited studies were conducted to comprehend WBV impact on individuals engaged in dynamic activities. This study explored the effects of different horizontal WBV frequencies on gait parameters, lower limb kinematics, and the cognitive response of healthy subjects. Forty participants walked at constant speed on a treadmill mounted on a horizontal shaker providing harmonic vibration with an amplitude of 1 m/s2 and frequencies 2–10 Hz, with inversely proportional amplitudes. A Psychomotor Vigilance Test measured reaction time while a motion capture system recorded walking kinematics. ANOVA results revealed no significant impact of vibration frequencies on the reaction time. At 2 Hz, alterations in gait spatiotemporal parameters were significant, with reduced stride length, stride time, step length, and stance time and increased step width and cadence. Similarly, gait variability measured by standard deviation and coefficient of variation significantly increased at 2 Hz compared to the other conditions. Comparably, kinematic time series analyzed through statistical parametric mapping showed significant adjustments in different portions of the gait cycle at 2 Hz, including increased hip abduction and flexion, greater knee flexion around the heel strike, and augmented ankle dorsiflexion. Participants exhibited gait kinematic variations, mainly at 2 Hz, where the associated mediolateral displacement was higher, as a plausible strategy to maintain stability and postural control during perturbed locomotion. These findings highlight individuals’ complex biomechanical adaptations in response to horizontal WBV, especially at lower frequencies, under dual-task conditions.

Nonlinear adaptive robust control with continuous error reduction mapping

Abstract Achieving high stability and high-precision control by traditional control algorithms is difficult due to the strong nonlinearity, parameter uncertainty, and random disturbance characteristics of electro-hydraulic proportional servo systems. Herein, we developed a nonlinear adaptive control algorithm based on Lyapunov functions. By estimating the parameters and converging their errors, this algorithm solved the parameter adaptation problem. Additionally, based on convergence inference from the nonnegativity of the derivative of Lyapunov functions, the algorithm designed a disturbance mapping through the derived function. The random disturbance was reduced through the mapping, improving the stability of the system under random disturbance. Finally, we carried out continuous derivation and moved the mapping relationship out of the intermediate temporary controller. This reduced the complexity of the calculation during controller design, prevented performance degradation of the error convergence algorithm after complex calculation, and enhanced the robustness of the algorithm. The algorithm was verified through the simulation model established by Simulink and experience. Results showed that the nonlinear adaptive control algorithm demonstrates fast response, high accuracy, and strong anti-interference ability compared with the high-gain robust control algorithm. It realizes the adaptation of unknown parameters and reduces the control error introduced by random disturbance.

Post-Impact Stability Control for Road Vehicles: State-of-the-Art Methodologies and Perspectives

Post-Impact Stability Control for Road Vehicles: State-of-the-Art Methodologies and Perspectives

AI-Driven Solar Energy Generation and Smart Grid Integration A Holistic Approach to Enhancing Renewable Energy Efficiency

This paper comprehensively analyzes AI-driven solar energy generation and smart grid integration, focusing on enhancing renewable energy efficiency. The study examines applying advanced artificial intelligence techniques in optimizing solar power production, forecasting, and grid management. Machine learning algorithms, including Support Vector Regression (SVR) and Artificial Neural Networks (ANN), are evaluated for effectiveness in solar irradiance prediction and PV system performance estimation. The integration of AI in smart grids is explored, highlighting its role in demand-side management, energy storage optimization, and grid stability control. A holistic approach to improving renewable energy efficiency is proposed, encompassing integrated AI frameworks for solar-plus-storage systems, multi-objective optimization techniques for energy management, and AI-enabled microgrids and virtual power plants. The paper also addresses the challenges and future trends in AI application to renewable energy systems, including scalability issues, regulatory considerations, and ethical implications. By leveraging big data analytics and advanced AI algorithms, this research demonstrates the potential for significant improvements in overall system efficiency, reliability, and sustainability of solar energy systems integrated with smart grids.

Interacting multiple model-based yaw stability control for distributed drive electric vehicle via adaptive model predictive control algorithm

The vehicle lateral stability control is a challenging problem due to the tire nonlinearity and the immeasurable sideslip angle. Thus, an adaptive model predictive control (AMPC) scheme based on interacting multiple model (IMM) vehicle sideslip angle observer is proposed in this paper. First, the observer is composed of the Extended Kalman filter (EKF) and the Unscented Kalman filter (UKF), which improves the real-time performance as well as the observation accuracy. Then, a multi-objective controller based on adaptive vehicle model prediction is designed using model predictive control algorithm. This controller aims to achieve a balance between the actuation and state constraints. The T-S fuzzy algorithm is used to observe the tire cornering stiffness and design an adaptive vehicle model. By utilizing the appropriate objective function and a quadratic programing solver, the controller output is obtained to achieve vehicle stability control. Finally, the effectiveness of the designed AMPC scheme under various working conditions is verified by Carsim-Simulink joint simulation platform and hardware-in-the-loop (HIL) test.

Improving cyber-physical-power system stability through hardware-in-loop co-simulation platform for real-time cyber attack analysis

With advancements in communication systems and measurement technologies, smart grids have become more observable and controllable, evolving into cyber-physical-power systems (CPPS). The impact of network security and secondary equipment on power system stability has become more evident. To support the existing grid toward a smart grid scenario, smart metering plays a vital role at the customer end side. Cyber-Physical systems are vulnerable to cyber-attacks and various techniques have been evolved to detect a cyber attack in the smart grid. Weighted trust-based models are suggested as one of the most effective security mechanisms. A hardware-in-loop CPPS co-simulation platform is established to facilitate the theoretical study of CPPS and the formulation of grid operation strategies. This paper examines current co-simulation platform schemes and highlights the necessity for a real-time hard-ware-in-the-loop platform to accurately simulate cyber-attack processes. This consideration takes into account the fundamental differences in modeling between power and communication systems. The architecture of the co-simulation platform based on RT-LAB and OPNET is described, including detailed modeling of the power system, communication system, and security and stability control devices. Additionally, an analysis of the latency of the co-simulation is provided. The paper focuses on modeling and implementing methods for addressing DDOS attacks and man-in-the-middle at-tacks in the communication network. The results from simulating a 7-bus system show the effectiveness and rationality of the co-simulation platform that has been designed.

3D Chaotic Nonlinear Dynamic Population-Growing Mathematical System Modeling with Multiple Controllers

Modeling, stabilization, and identification processes are significant stages in the process of developing knowledge about chaotic dynamical systems which entail the effective prediction depending on the degree of uncertainty toleration in the forecast, accuracy of the current state to be measured as well as a time scale resting on the dynamics of the system. Control of under-activated dynamical systems has been considered substantially, and it is for periods and is currently developing in various domains such as biology, data analysis, computing systems, and so forth. Dynamic systems of growing population signifies a model describing the way a population evolves over time during which population goes through major life events, split into discrete time periods. The size of the population at a given time period is determined by the rate of growth as well as other related factors. Most progress has been made in model-based control theory, which has drawbacks when the system under consideration is exceedingly complicated, and no model can be constructed. Accordingly, a 3D-discrete and dynamic human population growth system with many controllers is proposed by examining the stability and symmetry of controller system clarifications. The symmetric stability control results are presented by considering a special parametric dynamic system in its coefficients besides suggesting periodic functional coefficients in terms of sin and cos functions. The controllers have the ability to reduce population growth rate unpredictability or enhance system stability under various external conditions. The unique and very effective strategies in relevant domains could provide a deeper understanding of their impact as well as the theoretical or technological innovations thereof. These controllers are capable of reducing population growth rate unpredictability or improving system stability under various external conditions, and applicable strategies in the relevant domains can provide profound comprehension over the impact along with the theoretical as well as technological advancements.

Parenting Attitudes and Attributional Style in the First Secondary School Students of kazeron City

Objectives: One of the most important factors affecting the psychological and educational performance of students is the documentation style. Parenting has a significant effect on the attributional style of students. This study was conducted with the aim of investigating the relationship between fathers’ parenting attitudes (authoritative, authoritarian, permissive) and attributional style (internality (locus), stability, globality) in high school students. Results: The results show that there is a positive and significant relationship between authoritative attitude and the dimension of totality and internality (locus), and there is also a negative and significant relationship between the parenting attitude of authoritarian and the dimension of stability in a negative situation (p&lt;0.001). There is no significant relationship between authoritarian parenting attitude and general dimensions and internality (locus), and a positive and significant relationship has been observed between authoritarian attitude and the style of sustainability documents in a negative situation (p&lt;0.001). There is a significant relationship between the permissive attitude and general attribution styles, internality (locus) and stability control (positive situation) (p&lt;0.001). Similarly, there is no significant difference between boys and girls in terms of parenting attitudes (authoritative, authoritarian, permissive). Conclusion: It seems that there is a significant relationship between the two parenting attitudes of authoritative and permissive of fathers with the attribution styles (internality (locus), stability, globality) of students.

Finite-time stability control with hardware-in-the-loop testing of a chaotic permanent magnet synchronous motor

Stability of Permanent Magnet Synchronous Motor (PMSM) is of prime importance for the successful operation of the drive system, which is found to be dependent on initial operating conditions showing chaotic characteristic. Therefore, the paper presents the stabilization of a chaotic PMSM system through the finite-time stability approach. From this aspect, three controllers have been developed which are effective for the suppression of machine chaotic behaviour. Proposed controllers are simpler and numerically stable in comparison with previous works. Furthermore, performance comparisons of the proposed controllers are also presented in term of their settling time and peak overshoot. Selection among the proposed controllers depends on the consideration of a particular operating index (settling time or peak overshoot) wherein, performance also varies on system parameter λ. Performance evaluation of proposed controllers has been presented in MATLAB environment. In order to validate the obtained MATLAB results, a real-time analysis has been carried out using Typhoon Hardware-in-the-loop (HIL) emulator. The comparison shows that both results follow the same trend and are closely coordinated with each other, which validates the proposed controllers.