System Dynamic Performance Research Articles

Model-Free Adaptive Control of an Active Half-Vehicle-Seat System Coupled with a Nonlinear Energy Sink Inerter (NESI)

In order to reduce vehicle vibration and improve vehicle ride comfort and handling stability, a nonlinear energy sink inerter (NESI) is designed by combing an inerter and nonlinear energy sink (NES) for use in the seat suspension and vehicle suspension for the half-vehicle-seat (HVS) system; furthermore, a model-free adaptive control (MFAC) method based on the genetic algorithm is proposed to enhance the dynamic performance of the passive HVS system. The dynamic model of the active HVS system coupled with NESI using the MFAC method is established; its dynamic responses under pavement random and shock excitations are acquired using the numerical method and the dynamic performance is evaluated by seven evaluation indicators. The efficacy of the MFAC method is demonstrated through comparative analysis with the original passive HVS system, the HVS system coupled with NESI, and the active HVS system coupled with NESI using the proportional integral derivative (PID) control method. In addition, the influence of the installed position of MFAC on the dynamic performance of the active HVS system coupled with NESI is examined. The results show that for the active HVS system coupled with NESI using the MFAC method, compared with the other three HVS systems, the root mean square (RMS) values of the vehicle body vertical acceleration, vehicle body pitch acceleration, seat vertical acceleration, and front and rear suspension dynamic travel under pavement random excitation are smaller, the corresponding peak amplitudes under pavement shock excitation reduce, and the vibration attenuation time shortens; the RMS values of the front and rear dynamic tire loading under pavement random excitation are slightly smaller, the corresponding peak amplitudes under pavement shock excitation increase, and the vibration attenuation time decreases, which reflects the best dynamic performance among the four HVS systems and shows the effectiveness of the MFAC method. Furthermore, the control effect of the MFAC method is the best when it acts both on the seat and vehicle suspensions.

Performance Evaluation of Solar PV Integrated with Custom Power Device under Various Load Conditions

The non-linear properties and rapid switching of power electronic equipment are the primary causes of power quality issues in power systems, particularly in the power distribution systems. The widespread use of delicate equipment, which continuously pollutes the environment, is making power quality problems worse. The increasing integration of renewable energy sources into the generation mix and the decarburization of the economy have created new challenges for smart grid technology, requiring creative solutions such as energy storage systems and smart transformers. This article describes a solar photovoltaic integrated unified power quality conditioner (UPQC) that uses a deep learning method based on neural networks and a novel compensating technique. Here, two Deep Neural Network algorithms are used, one in the solar PV system to obtain the maximum power under various irradiance situations, and the other to manage the UPQC under various load conditions. When compared to the conventional UPQC based on PQ Theory, DNN-UPQC produces superior results in terms of reducing total harmonic distortion. This iterative strategy, which is focused on soft computing, provides faster convergence to the target condition while maintaining the updating weight within a predetermined limit. PV-based UPQC has been connected individually to reduce voltage sag, swell, and unbalance in variable load conditions. The system's dynamic and steady state performance are assessed by modelling it with a MATLAB-Simulink in different load condition.

Dynamic Obstacle Avoidance Technology Based on Multi-Sensor Fusion in Autonomous Driving

With the booming development of artificial intelligence and sensor technology, various types of devices are widely used in daily life and industry. This paper reviews the current state and prospects of multi-sensor fusion technology for dynamic obstacle avoidance in autonomous systems. The purpose of this paper is to discuss the application status and future development direction of multi-sensor fusion technology in dynamic obstacle avoidance. By analyzing the current research results and technical challenges, this paper will summarize how multi-sensor fusion technology can improve the performance of dynamic obstacle avoidance systems, and discuss the application of intelligent algorithms and future research directions The limitations of traditional single-sensor approaches are demonstrated through a single-sensor versus multi-sensor comparison, emphasizing the advantages of combining data from various sensors (e.g. lidar, cameras, and IMUs) to enhance environmental perception. This fusion improves obstacle detection accuracy and system robustness, particularly in complex urban environments. Despite significant advancements, challenges remain, including data management, real-time processing, and computational efficiency.

A quantitative characterization model for nonlinear dynamic parameters of O-rings

When the rubber O-ring follows the primary seal in the axial direction as a secondary seal, there is hysteresis behavior between the restoring force and displacement. However, the dynamic parameters of O-rings are mostly expressed as constants in dynamic analysis at present, which cannot accurately describe the dynamic behavior of sealing systems. In response to the problem of poor track performance of mechanical seals, based on the actual working conditions in nuclear reactor coolant pumps, vibration experiments with high pressure and water lubrication are carried out on ethylene-propylene-diene monomer (EPDM) rubber O-rings, which can reveal the laws in the actual situation. The experimental results confirm that there are nonlinear variations of O-ring dynamic parameters in vibration, which cannot be expressed by constants. In order to quantitatively characterize the nonlinear behavior, this study establishes a novel mathematical model and analyze the influence of working conditions. A method combining the nonlinear properties of both interfacial sliding and body viscoelasticity of O-rings is proposed. The nonlinear stiffness, damping and friction (NSDF) model is established based on the adjusted Iwan model and the trace method. The finite element analysis and vibration experiments are carried out to study the hysteretic behavior and determine the parameters of the model. Furthermore, the influence of medium pressure and vibration amplitude on interfacial stiffness and O-ring stiffness and damping are discussed. It is pointed out that O-ring stiffness and damping decrease with increasing amplitude and increase with increasing pressure. The comparative analysis of experiments and model shows that the proposed model can provide an accurate determination of the nonlinear behavior of O-rings in vibration. The results and the proposed model can provide a basis for the evaluation of the dynamic performance of mechanical seal systems.

Analyzing vibration transmission through cantilever systems using biomechanical and impact-responsive metamaterial structures

Vibration control in cantilever systems is a critical challenge in various engineering applications, where unwanted vibrations can lead to structural fatigue, reduced performance, and potential failure. This study investigates the effects of integrating biomechanical and impact-responsive metamaterials into cantilever systems to mitigate vibration transmission. The metamaterials, characterized by their adaptive stiffness and energy-absorbing properties, are strategically embedded in key structural components such as the arms, joints, and base. Through experimental analysis, this work assesses the reduction in vibration amplitude, shifts in natural frequency, enhanced damping capacity, energy absorption during impact, and strain reduction at critical points. The results show that the metamaterial-enhanced system achieves significant reductions in vibration amplitude, up to 40%, and increases in natural frequency by over 30%, minimizing the risk of resonance. Additionally, the damping ratio is improved by as much as 53%, while the energy absorption during impact is increased by up to 26%. Strain reduction at critical points reaches 24%, contributing to improved mechanical resilience. These findings demonstrate the potential of biomechanical and impact-responsive metamaterials in enhancing the dynamic performance of cantilever systems, offering a new approach to vibration mitigation in engineering applications.

Enhancing Multi-Machine Power System Stability with STATCOM-SMES: A Soft Computing Approach

The increasing complexity and increasing mismatch between supply and demand within modern power systems necessitate advanced methods for ensuring system stability and reliable operation. This article investigates the enhancement of transient stability in a multi-machine power system through the integration of Flexible AC Transmission Systems (FACTS) devices, specifically a Static Synchronous Compensator (STATCOM) combined with energy storage. Leveraging soft computing techniques such as Fuzzy Logic Controllers (FLC) and Artificial Neural Networks (ANN), this study evaluates the performance improvements in transient stability. The methodology involves modeling a multi-machine power system, implementing STATCOM-SMES configurations, and designing FLC and ANN controllers to dynamically support system stability. Simulations are conducted using MATLAB/Simulink, applying a three-phase to ground fault to assess the system's transient response. Performance metrics such as peak overshoot, settling time, and damping ratio are analyzed to compare the effectiveness of the proposed techniques. The results demonstrate significant improvements in transient stability with the application of FLC and ANN controlled STATCOM-SMES systems. This study underscores the potential of integrating soft computing techniques with FACTS devices to enhance the dynamic performance and resilience of power systems, contributing valuable insights for future research and practical applications in power system stability.

Correction: Theoretical Investigation into the Dynamic Performance of a Solar-Powered Multistage Water Gap Membrane Distillation System

Correction: Theoretical Investigation into the Dynamic Performance of a Solar-Powered Multistage Water Gap Membrane Distillation System

Dynamic response and power performance of a combined semi-submersible floating wind turbine and point absorber wave energy converter array

With the global demand for renewable energy rising, offshore renewable energy development has gained more attention. The combination of wind and wave energy is a new trend. Ensuring stability in combined systems is crucial for efficiency of absorbing energy. A novel combined wind and wave energy system with a semi-submersible floating wind turbine (FWT) and an array of six torus-shaped point absorber wave energy converters (WECs) is proposed. The dynamic response of combined system is investigated using 3D potential flow theory by comparing to the original system. The effects of power take-off (PTO) damping, WEC float shape and seasonal variation on the dynamic response and power performance of combined system are studied. The results show that the addition of WEC array improves the stability and power production of combined system. Meanwhile, the total power of combined system is approximately 2.5%–6.5 % higher than that of original system. PTO damping mainly affects the heave motion of combined system. As PTO damping increases, the first peak of mean power of WEC array shifts towards the long period, while the second peak of that shifts towards the short period. The conical-bottom WEC generates the most power compared to the flat-bottom WEC, hemispherical-bottom WEC and concave-bottom WEC. The combined system generates the most power in winter, and the total annual electricity output can be up to 2.99 × 104 MWh.

Integral Sliding Mode‐Composite Nonlinear Feedback Control Strategy for Microgrid Inverter Systems

To enhance the dynamic performance and robustness of the voltage control system of islanded microgrid inverters, a new control strategy combining integral sliding mode (ISM) control and composite nonlinear feedback (CNF) control is proposed. In ISM control, firstly, a new reaching law is designed to improve movement quality in the reaching phase by improving the power term and introducing the inverse tangent function. Then, to improve disturbance observation accuracy, a variable gain extended state observer is designed by improving the regulation mechanism of the state variables according to deviation control. Using the idea of variable damping, linear and nonlinear feedback are combined into CNF control. Specifically, linear feedback provides a small damping ratio for faster system response, while nonlinear feedback increases the damping ratio to improve steady‐state performance. Simulation results show that the integral sliding mode‐composite nonlinear feedback (ISM‐CNF) control strategy cam balances convergence speed and chattering better and achieves higher steady‐state accuracy than conventional strategies. Moreover, ISM‐CNF control has better robustness to reference voltage variations and disturbances caused by sudden load changes. Therefore, the ISM‐CNF control strategy can accomplish voltage control of islanded microgrid inverters quickly and steadily, effectively suppressing system disturbances and enhancing stability and power quality. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

System Identification for Robust Control of an Electrode Positioning System of an Industrial Electric Arc Melting Furnace

Through system identification for robust control methods and utilizing real-time experimental field data, a comprehensive mathematical model is derived that represents the dynamic performance of a single electrode positioning system (EPS) in an industrial electric arc melting furnace (EAF). This EPS is characterized by large, time-varying dynamic parameters, which fluctuate based on operating conditions, specifically as the electrode weight changes within its operational range. The system identification methodology for robust control is developed in four main steps, progressing from experimental design to model validation. This approach yields a nominal model of the actual system and provides a trustworthy estimate of the region of uncertainty of the model, bounded by models of the real system under maximum and minimum electrode weight conditions (limit operating models). The methodology generates three fourth-order time-delay models using an ARMAX structure. The results are promising, as system identification for robust control enables the derivation of mathematical models specifically tailored for designing robust controllers. These controllers significantly enhance the EPS control system’s performance and substantially reduce energy consumption and environmental emissions.

Review of PID Control in Industrial Areas for Tobacco Production, Self-driving Car Technology and Robotic Arm Robots

Abstract. PID control is widely employed across diverse industries such as tobacco production, autonomous car technology, and mechanical arm robotics. This shows that PID control has a substantial developmental potential, so I choose the PID control as the topic. Since few people summarize its different applications in different industries, this study has the motivation to comprehensively summarize the applications of PID. This research provides an in-depth overview and analysis of PID control's varied applications in tobacco production, autonomous car technology, and mechanical arm robotics. It focuses on addressing practical challenges and exploring optimization strategies encountered in these fields. This article is summarized using the methods of the review. PID plays a crucial role in enhancing stability, precision, and response speed in these applications, thereby improving overall control system dynamic response performance. This study consolidated existing literature to offer insights into PID's effectiveness across these industrial sectors, shedding light on its impact and potential for further advancements in control technology.

Transient investigation of a residential building air conditioning system with heat pump and PV/T modules

Abstract Nowadays, in response to the European energy crisis and the imperative to reduce carbon emissions, the study of energy systems plays a crucial role. New energy systems and configurations have been studied in the recent years to improve the energy efficiency and reduce greenhouse gases emissions. This study investigates the dynamic performance of a residential HVAC system integrating photovoltaic thermal (PV/T) modules and a heat pump. The system aims to harness thermal energy from solar radiation using PV/T modules to generate electricity and heat water. The case study is performed considering a building located in Caserta. According to the authors knowledge, there is a lack of information regarding the modeling of PV/T systems with a heat pump. Inside the studied system, the thermal energy is stored in a storage tank for later use. An auxiliary heater is activated to produce domestic hot water (DHW) when the PV/T cannot provide it. The system components are modeled using TRNSYS. A dynamic simulation approach is adopted to assess the system performance under varying environmental conditions and building load demands. These load demands are used to model real-world scenarios. This kind of system offers several advantages. Firstly, the PV/T modules serve a dual purpose of electricity generation and water heating, maximizing energy utilization. Secondly, the heat pump enhances the overall efficiency of the system by extracting heat from the water stored in the puffer tank, thereby reducing reliance on conventional heating methods. The findings of this study provide valuable insights into the performance and feasibility of integrating PV/T in residential HVAC systems. During the winter season, the solar fraction, the ratio between energy supply from PV/T and total energy demand, averages about 25%. When heating is not required, the PV/T panels manage to ensure the production of approximately 75% of DHW.

Dynamic analysis of a high-speed micro compressor supported by spiral-grooved hydrodynamic air bearing

Spiral-grooved hydrodynamic air bearings are used in high-speed machines due to their advantages of oil-free, low friction, and compact structure. This paper aims to investigate the dynamic characteristics of a high-speed rotor supported by spiral-grooved hydrodynamic air bearings and the effects of spiral groove parameters. A mathematical model of the rotor-bearing system is developed by coupling the rotor nonlinear motion equations and the bearing dynamic Reynolds equation. The finite element method combined with the Runge-Kutta method is employed simultaneously to obtain the nonlinear trajectory of the rotor-bearing system. The theoretical model is verified by experiments on the built micro compressor prototype. The numerical predicted onset speed of the sub-synchronous motion of the rotor-bearing system agrees well with the experimental observations. Furthermore, the effects of radius clearance, groove depth, groove angle, groove axial and circumferential width on the dynamic performance of the rotor-bearing system are analyzed. The results show that radius clearance has the most significant influence, followed by groove depth, groove axial, and then circumferential width. The groove angle has the least impact.

Design and Control of Single-Phase Double-Stage PV-MPPT System

In the double-stage Photovoltaic-Maximum Power Point Tracking (PV-MPPT) systems, the performance of each stage and the MPPT algorithm may affect the system performance. This study gives the design and control of a single-phase double-stage PV-MPPT system with a cascade controller. For the DC-link voltage control, a classical PI controller is employed. However, double-line frequency harmonic emerges inherently in the DC-link voltage. This voltage harmonic causes a third harmonic in the injected grid current. Therefore, a proportional multi-resonant controller is used in the inner current loop controller to control the grid current and suppress the third harmonic. The designed system's steady-state and dynamic performance are tested under different PV power and sudden power changes. The simulation results show that the injected grid current is in phase with the grid voltage and has a low THD value. Also, the DC-link voltage is stable under even sudden power changes. The results prove the effectiveness of the designed system.

Fast Iterative Sample Transfer Identification Method for Dynamic Systems Under Non‐identical Distribution

ABSTRACTThis paper proposes a method to improve the identification performance of linear dynamic systems by utilizing knowledge from samples of non‐identical distribution systems. Traditional identification methods heavily rely on the quality of the dataset, such as sample length and noise level, which constrains their performance due to the assumption of identical distribution. Motivated by the concept of sample‐based transfer learning, we propose a sample transfer identification method and derive the condition to avoid negative transfer. We develop a fast iterative transfer identification method for low storage costs, considering the computational burden imposed by the sample size from the source system. Additionally, based on the fast iterative transfer identification method, considering the need to update the current measurement data model in real time, a fast iterative online sample transfer identification method is explored. Through simulations, we validate the effectiveness and superiority of the proposed methods. The results show that sample transfer identification is superior to non‐transfer identification and fast iterative sample transfer identification effectively reduces the calculation amount when dealing with low quality measurement data.

Inverse chance-constrained dynamic data envelopment analysis under natural and managerial disposability: Concerning renewable energy efficiency and potentials

The performance of dynamic systems with specific data has been examined in some data envelopment analysis (DEA) studies. However, in many real-life situations, dealing with dynamic systems becomes challenging because of random factors. So, in this paper, a chance-constrained dynamic DEA approach under managerial and natural disposability is first proposed to analyze the dynamic renewable energy efficacy of processes in the presence of random performance measures. Then, the potentials of some performance metrics are addressed for changes of others using the introduced inverse chance-constrained dynamic DEA models. The chance-constrained dynamic DEA techniques and their inverse dynamic stochastic problems are converted into linear problems. The introduced approaches are applied to probe the renewable energy efficiency and potentials of some OECD countries in a span of time. The results show stochastic dynamic DEA and inverse stochastic dynamic DEA provided are practical tools for making the best choices, when there is uncertainty.

A Novel Numerical Approach to Investigate Shaft Diameter Effect on Dynamic Behaviour of Multi-Disc Rotors

In this study, a displacement-based finite element model was developed to investigate the effect of the diameter of rotating shafts on dynamic performance of a multi-disc rotor system with respect to their natural frequencies and critical speeds. The variation in rotor bearing stiffness was considered in this study. A numerical case study that simulating a typical rotating machine was adopted to assess the present methodology. The results obtained show that the diameter of the rotor has a significant effect on the rotor dynamic characteristics. The amount of the influence was found to be highly sensitive to bearing stiffness of the rotating machine. An experimental setup was constructed and tests were performed to validate the applicability of the numerical model. The reasonable agreement found between the results obtained numerically and experimentally validates the proposed numerical model.

A Novel Feedforward Scheme for Enhancing Dynamic Performance of Vector-Controlled Dual Active Bridge Converter with Dual Phase Shift Modulation for Fast Battery Charging Systems

This paper proposes a novel feedforward control scheme to achieve a very smooth transition from Constant Current (CC) to Constant Voltage (CV) charging modes, the commonly used method for electric vehicle charging applications. Furthermore, a three-loop model-independent Linear Active Disturbance Rejection Control (LADRC)-based system is proposed, replacing the traditional two-loop Proportional-Integral (PI) control system. The extra loop performs a decoupled dq vector control of the inductor current, which is typically not used in single-phase Dual Active Bridge (DAB) systems. This additional loop not only facilitates the optimal determination of both internal and external phase shift angles of a Dual-Phase Shift (DPS) modulator but also lowers the peak input current of the converter, allowing for lower-rated switches. Numerical simulations using MATLAB/Simulink demonstrate the robustness of the proposed control strategy against both input voltage disturbances and load disturbances during the transition from CC to CV charging modes. Hence, the dynamic performance of the charging system is significantly improved with minimal controller effort.

A Method for Optimizing Terminal Sliding Mode Controller Parameters Based on a Multi-Strategy Improved Crayfish Algorithm

This paper proposes a parameter optimization method for a terminal sliding mode controller (TSMC) based on a multi-strategy improved crayfish algorithm (JLSCOA) to enhance the performance of ship dynamic positioning systems. The TSMC is designed for the “Xinhongzhuan” vessel of Dalian Maritime University. JLSCOA integrates subtractive averaging, Levy Flight, and sparrow search strategies to overcome the limitations of traditional crayfish algorithms. Compared to COA, WOA, and SSA algorithms, JLSCOA demonstrates superior optimization accuracy, convergence performance, and stability across 12 benchmark test functions. It achieves the optimal value in 83% of cases, outperforms the average in 83% of cases, and exhibits stronger robustness in 75% of cases. Simulations show that applying JLSCOA to TSMC parameter optimization significantly outperforms traditional non-optimized controllers, reducing the average time for three degrees of freedom position changes by over 300 s and nearly eliminating control force and velocity oscillations.

Dynamic Characteristics Analysis of the DI-SO Cylindrical Spur Gear System Based on Meshing Conditions

The dual-input single-output (DI-SO) cylindrical spur gear system possesses advantages such as high load-carrying capacity, precise transmission, and low energy loss. It is increasingly becoming a core component of power transmission systems in maritime vessels, aerospace, marine engineering, and construction machinery. In practical operation, the stability of the DI-SO cylindrical spur gear system is influenced by complex excitations. These excitations lead to nonlinear vibration, meshing instability, and noise, which affect the performance and reliability of the entire equipment. Hence, the dynamic performance of the DI-SO cylindrical spur gear system is thoroughly investigated in this research. The impact of excitations and nonlinear factors on the dynamic characteristics was investigated comprehensively. A comparative analysis of the gear system was conducted by establishing a bending–torsional coupling vibration analysis model under synchronous and asynchronous meshing conditions. Nonlinear factors such as periodic time-varying meshing stiffness, meshing damping, friction coefficient, friction arms, load sharing ratio, comprehensive transmission error, and backlash were considered in the proposed model. Then, the effect laws of excitations and nonlinear factors such as meshing frequency, driving load fluctuation, backlash, and comprehensive transmission error were analyzed. The results indicate that the dynamic characteristics exhibited staged stable and unstable states under different meshing frequencies and meshing conditions. At the medium-frequency meshing stage (0.96 × 104~1.78 × 104 Hz), alternating phenomena of multi-periodic, quasi-periodic, and chaotic motion states were observed. Moreover, the root mean square value (RMS) of the dynamic transmission error (DTE) in the asynchronized gear system was generally higher than that in the synchronized gear system. It was found that selecting the appropriate meshing condition could effectively reduce the amplitude of the DTE. Additionally, the dynamic performance could be significantly improved by adjusting control parameters such as driving load fluctuation (0~179 N), backlash (0.8 × 10−4~0.9 × 10−4 m), and comprehensive transmission error (7.9 × 10−4~9.4 × 10−4 m). The research results provide a theoretical guidance for the design and optimization of the DI-SO cylindrical spur gear system.