Search Results (356)

Understanding flow dynamics in open-channel node systems is crucial for designing effective hydraulic engineering solutions and minimizing energy losses. This study investigates how junction geometry—specifically the lateral inflow angle (α = 45° and 60°) and the longitudinal bed slope (I = 0.0011 to 0.0051)—influences the water velocity distribution and hydraulic losses in a rigid-bed Y-shaped open-channel junction. Experiments were performed in a 0.3 m wide and 0.5 m deep rectangular flume, with controlled inflow conditions simulating steady-state discharge scenarios. Flow velocity measurements were obtained using a PEMS 30 electromagnetic velocity probe, which is capable of recording three-dimensional velocity components at a high spatial resolution, and electromagnetic flow meters for discharge control. The results show that a lateral inflow angle of 45° induces stronger flow disturbances and higher local loss coefficients, especially under steeper slope conditions. In contrast, an angle of 60° generates more symmetric velocity fields and reduces energy dissipation at the junction. These findings align with the existing literature and highlight the significance of junction design in hydraulic structures, particularly under high-flow conditions. The experimental data may be used for calibrating one-dimensional hydrodynamic models and optimizing the hydraulic performance of engineered channel outlets, such as those found in hydropower discharge systems or irrigation networks. Full article

Magnetocardiography (MCG) offers a noninvasive method for early screening and precise localization of cardiovascular diseases by measuring picotesla-level weak magnetic fields induced by cardiac electrical activity. However, in unshielded magnetic environments, geomagnetic disturbances, power-frequency electromagnetic interference, and physiological/motion artifacts can significantly overwhelm effective magnetocardiographic components. To address this challenge, this paper systematically constructs an integrated denoising framework, termed “AOA-VMD-WT”. In this approach, the Arithmetic Optimization Algorithm (AOA) adaptively optimizes the key parameters (decomposition level K and penalty factor α) of Variational Mode Decomposition (VMD). The decomposed components are then regularized based on their modal center frequencies: components with frequencies ≥50 Hz are directly suppressed; those with frequencies <50 Hz undergo wavelet threshold (WT) denoising; and those with frequencies <0.5 Hz undergo baseline correction. The purified signal is subsequently reconstructed. For quantitative evaluation, we designed performance indicators including QRS amplitude retention rate, high/low frequency suppression amount, and spectral entropy. Further comparisons are made with baseline methods such as FIR and wavelet soft/hard thresholds. Experimental results on multiple sets of measured MCG data demonstrate that the proposed method achieves an average improvement of approximately 8–15 dB in high-frequency suppression, 2–8 dB in low-frequency suppression, and a decrease in spectral entropy ranging from 0.1 to 0.6 without compromising QRS amplitude. Additionally, the parameter optimization exhibits high stability. These findings suggest that the proposed framework provides engineerable algorithmic support for stable MCG measurement in ordinary clinic scenarios. Full article

The electrification of agricultural equipment is a critical pathway to address the dual challenges of increasing global food production and ensuring sustainable agricultural development. As the core power unit, the permanent magnet synchronous motor (PMSM) drive system faces severe challenges in achieving high performance, robustness, and reliable control in complex farmland environments characterized by sudden load changes, extreme operating conditions, and strong interference. This paper provides a comprehensive review of key technological advancements in PMSM drive systems for agricultural electrification. First, it analyzes solutions to enhance the reliability of power converters, including high-frequency silicon carbide (SiC)/gallium nitride (GaN) power device packaging, thermal management, and electromagnetic compatibility (EMC) design. Second, it systematically elaborates on high-performance motor control algorithms such as Direct Torque Control (DTC) and Model Predictive Control (MPC) for improving dynamic response; robust control strategies like Sliding Mode Control (SMC) and Active Disturbance Rejection Control (ADRC) for enhancing resilience; and the latest progress in fault-tolerant control architectures incorporating sensorless technology. Furthermore, the paper identifies core challenges in large-scale applications, including environmental adaptability, real-time multi-machine coordination, and high reliability requirements. Innovatively, this review proposes a closed-loop intelligent control paradigm encompassing environmental disturbance prediction, control parameter self-tuning, and actuator dynamic response. This paradigm provides theoretical support for enhancing the autonomous adaptability and operational quality of agricultural machinery in unstructured environments. Finally, future trends involving deep AI integration, collaborative hardware innovation, and agricultural ecosystem construction are outlined. Full article

Random number generators play a critical role in ensuring information security, supporting encrypted communications, and preventing data leakage. However, the random number generators widely used in hardware are faced with potential threats such as environmental disturbances and fault injection attacks. Especially in automotive-grade environments, chips encounter threat scenarios involving multidimensional fault injection, which may lead to functional failures or malicious exploitation, endangering the security of the entire system. This paper focuses on a Counter Mode Deterministic Random Bit Generator (CTR-DRBG) based on the AES-128 algorithm and implements a hardware prototype system compliant with the NIST SP 800-22 standard on an FPGA platform. Centering on typical fault modes such as temperature disturbances, voltage glitches, electromagnetic interference, and bit flips, single-dimensional and multidimensional fault injection and simulated fault injection experiments were designed and conducted. The impact characteristics and sensitivities of electromagnetic faults, voltage faults, and temperature faults regarding the output sequences of random numbers were systematically evaluated. The experimental results show that this type of random number generator exhibits modular-level differential vulnerability under physical disturbances, especially in the data transmission processes of encryption paths and critical registers, which demonstrate higher sensitivity to flip-type faults. This research provides a feasible analysis framework and practical basis for the security assessment and fault-tolerant design of random number generators, possessing certain engineering applicability and theoretical reference value. Full article

This study aims to develop an event-triggered control strategy of grid-connected inverters, based on the linear parameter-varying (LPV) modeling approach. Regarding the changes in grid voltage, filter capacitance and inductance, and random electromagnetic interference, a stochastic LPV model for three-phase two-level inverters is established. To reduce computation burden, an event trigger with a continuous-time form is adopted to derive the state feedback controller for the LPV plant. Unlike the existing common approach to dealing with event-triggered mechanisms, a predesignated event-triggering threshold is used to determine the triggering instant of the event condition. Using parameter-dependent Lyapunov functions, sufficient conditions reliant on parameters are introduced. Based on the derived conditions, the corresponding event-triggered controllers are engineered to ensure uniform ultimate bounded stability for the resulting event-triggered LPV inverter system subject to exogenous disturbance. The simulation results are presented to confirm the efficacy of the proposed methods. Full article

In the three-motor hybrid architecture, the auxiliary drive uses electrically excited synchronous motor (EESM), which has the advantages of high torque density, wide speed range and strong anti-demagnetization ability. However, the strong electromagnetic coupling between the field winding and the armature winding leads to the difficulty of current control, and the traditional PID has limitations in dynamic response and immunity. In order to solve this problem, a linear active disturbance rejection control (LADRC) method for the rotor of EESM is proposed in this paper, linear extended state observer (LESO) is used to estimate and compensate the system internal and external disturbances (such as winding coupling and parameter perturbation) in real time. The method only uses the input and output of the system and does not depend on any mechanical parameters, so that the torque response is improved by 50%, and the steady-state fluctuation is reduced by 10.2%. In addition, an adaptive dynamic programming (ADP) parameter optimization strategy is proposed to solve the bandwidth parameter tuning problem of LADRC algorithm in complex operating conditions, and the related mathematical analysis of optimality properties is given. Finally, the proposed method is compared with the traditional PI controller in several operating conditions of EESM, and the effectiveness of the proposed method is validated by the corresponding results. Full article

Smart monitoring of local electricity systems (LESs) with sources based on renewable energy resources (RESs) from the point of view of the requirements of the functions of an intelligent system are hardware and software systems that can solve the tasks of both analysis (optimization) and synthesis (design, planning, control). The article considers the following: a functional scheme of smart monitoring of LESs, describing its main components and scope of application; an assessment of the state of the processes and the state of the equipment of generators and loads; dynamic pricing and a dynamic assessment of the state of use of primary fuel and/or current costs of generators; economic efficiency of generator operation and loads; an assessment of environmental acceptability, in particular, the volume of CO₂ emissions; provides demand-side management, managing maximum energy consumption; a forecast of system development; an assessment of mutual flows of electricity; system resistance to disturbances; a forecast of metrological indicators, potential opportunities for generating RESs (wind power plants, solar power plants, etc.); an assessment of current costs; the state of electromagnetic compatibility of system elements and operation of electricity storage devices; and ensures work on local electricity markets. The application of smart monitoring in the formation of tariffs on local energy markets for transactive energy systems is shown by conducting a combined comprehensive assessment of the energy produced by each individual power source with graphs of the dependence of costs on the generated power. Algorithms for the comprehensive assessment of the cost of electricity production in a transactive system for calculating planned costs are developed, and the calculation of the cost of production per 1 kW is also presented. A visualization of the results of applying this algorithm is presented. Full article

With the increasing demand for high integration, low cost, and large capacities in satellite systems, integrating the antenna and microwave component into the same system has become appealing to the satellite engineer. The dual C-type gold ribbon, performing as the key electromagnetic signal bridge between the microwave component and the antenna, has a significant impact on the electrical performance of satellite antennas. However, during its manufacturing and operating, the interconnection geometry undergoes deformation due to mounting errors and environmental loads. Consequently, these parasitic geometry parameters can significantly increase energy loss during the signal transmission. To address this issue, this paper has proposed a method for determining the design range of the geometrical parameters of the dual C-type gold ribbon, and applied it to the performance prediction of the microstrip antennas and the parameter optimization of the gold ribbon. In this study, a mechanical response analysis of the antennas in the operating environment has been carried out and the manufacturing disturbance has been considered to calculate the geometry fluctuation range. Then, the significance ranking of the geometry parameters has been determined and the key parameters have been selected. Finally, the chaos feedback adaptive whale optimization algorithm–back propagation neural network has been used as a surrogate model to establish the relationship between the geometry parameters and the antenna electromagnetic performance, and the multi-objective red-billed blue magpie optimization algorithm has been combined with the surrogate model to optimize the configuration parameters. This paper provides theoretical guidance for the interconnection geometry design and the optimization of the integration module of the antennas and microwave components. Full article

This paper presents an electromechanical coupling model integrating an equivalent magnetic network (EMN) model of a dual three-phase permanent magnet synchronous motor (DTP-PMSM) with the dynamic model of a helical planetary gear transmission system. Using this model, this study analyzes the dynamic characteristics of an electric drive system, specifically motor phase current, electromagnetic torque, and gear meshing force, under self-fault-tolerant control strategies. Simulation and experimental results demonstrate that the self-fault-tolerant control strategy enables rapid fault tolerance during open-phase faults, significantly reducing system fault recovery time. Meanwhile, compared to the open-phase faults conditions, the self-fault-tolerant control effectively suppresses most harmonic components within the system; only the second harmonic amplitude of the electromagnetic torque exhibited an increase. This harmonic disturbance propagates to the gear system through electromechanical coupling, synchronously amplifying the second harmonic amplitude in the gear system’s vibration response. This study demonstrates that self-fault-tolerant control strategies significantly enhance the dynamic response performance of the electric drive system under open-phase faults conditions. Furthermore, this study also investigates the electromechanical coupling mechanism through which harmonics generated by this strategy affect the gear system’s dynamic response, providing theoretical support for co-optimization electromechanical coupling design and fault-tolerant control in high-reliability electric drive transmission systems. Full article

The force ripple of a permanent magnet synchronous linear motor (PMSLM) caused by multi-source disturbances in practical applications seriously restricts its high-precision motion control performance. The traditional single-mechanism model has difficulty fully characterizing the nonlinear disturbance factors, while the data-driven method has real-time limitations. Therefore, this paper proposes a hybrid modeling framework that integrates the physical mechanism and measured data and realizes the dynamic compensation of the force ripple by constructing a collaborative suppression algorithm. At the mechanistic level, based on electromagnetic field theory and the virtual displacement principle, an analytical model of the core disturbance terms such as the cogging effect and the end effect is established. At the data level, the acceleration sensor is used to collect the dynamic response signal in real time, and the data-driven ripple residual model is constructed by combining frequency domain analysis and parameter fitting. In order to verify the effectiveness of the algorithm, a hardware and software experimental platform including a multi-core processor, high-precision current loop controller, real-time data acquisition module, and motion control unit is built to realize the online calculation and closed-loop injection of the hybrid compensation current. Experiments show that the hybrid framework effectively compensates the unmodeled disturbance through the data model while maintaining the physical interpretability of the mechanistic model, which provides a new idea for motor performance optimization under complex working conditions. Full article

This work proposes an effective control technique for enhancing the stability of Doubly Fed Induction Generator-Based Wind Turbines (DFIG-WTs) connected to the grid during voltage sag and swell events, ensuring the reliable and efficient operation of wind energy systems integrated with the grid. The proposed approach integrates a Dynamic Voltage Restorer (DVR) in series with a Wind Turbine Generator (WTG) output terminal to enhance the Fault Ride-Through (FRT) capability during grid disturbances. To develop a flexible control strategy for both unbalanced and balanced fault conditions, a combination of feedforward and feedback control based on a sliding mode control (SMC) for DVR converters is used. This hybrid strategy allows for precise voltage regulation, enabling the series compensator to inject the required voltage into the grid, thereby ensuring constant generator terminal voltages even during faults. The SMC enhances the system’s robustness by providing fast, reliable regulation of the injected voltage, effectively mitigating the impact of grid disturbances. To further enhance system performance, Model Predictive Control (MPC) is implemented for the Rotor-Side Converter (RSC) within the back-to-back converter (BTBC) configuration. The main advantages of the predictive control method include eliminating the need for linear controllers, coordinate transformations, or modulators for the converter. Additionally, it ensures the stable operation of the generator even under severe operating conditions, enhancing system robustness and dynamic response. To validate the proposed control strategy, a comprehensive simulation is conducted using a 2 MW DFIG-WT connected to a 120 kV grid. The simulation results demonstrate that the proposed control approach successfully limits overcurrent in the RSC, maintains electromagnetic torque and DC-link voltage within their rated values, and dynamically regulates reactive power to mitigate voltage sags and swells. This allows the WTG to continue operating at its nominal capacity, fully complying with the strict requirements of modern grid codes and ensuring reliable grid integration. Full article

This manuscript proposes a fast transient simulation method based on PEEC to model overvoltage caused by spark gap and disconnecting switch operations in UHV series compensation (FSC). It proposes a simulation method based on the Partial Element Equivalent Circuit (PEEC) for modeling the fast transient processes associated with the operation of primary equipment in UHV FSC. Initially, a multi-conductor system model for both primary and secondary equipment on the cascade platform is developed. Then, the lumped components′ modeling of primary equipment and secondary equipment is added on the basis of multi-conductor model. Through simulation, the rapid transient overvoltage of primary equipment and the electromagnetic disturbance of the secondary system are analyzed. The simulation results provide insights into the distribution of fast transient overvoltage and the transient electromagnetic disturbance along the bus, from the low-voltage bus to the high-potential platform, under various primary equipment operating conditions. These findings provide a basis for theoretical analysis of the layout of sensor devices on platform and the design of electromagnetic shielding for interference-prone systems on platform. Full article

This paper presents a structured and experimentally validated approach to the parameter identification, modeling, and real-time speed control of a brushless DC (BLDC) motor. Electrical parameters, including resistance and inductance, were measured through DC and AC testing under controlled conditions, respectively, while mechanical and electromagnetic parameters such as the back electromotive force (EMF) constant and rotor inertia were determined experimentally using an AVL dynamometer. The back EMF was obtained by operating the motor as a generator under varying speeds, and inertia was identified using a deceleration method based on the relationship between angular acceleration and torque. The identified parameters were used to construct a transfer function model of the motor, which was implemented in MATLAB/Simulink R2024b and validated against real-time experimental data using sinusoidal and exponential input signals. The comparison between simulated and measured speed responses showed strong agreement, confirming the accuracy of the model. A proportional–integral (PI) controller was developed and implemented for speed regulation, using a low-cost National Instruments (NI) USB-6009 data acquisition (DAQ) and a Kelly controller. A first-order low-pass filter was integrated into the control loop to suppress high-frequency disturbances and improve transient performance. Experimental tests using a stepwise reference speed profile demonstrated accurate tracking, minimal overshoot, and robust operation. Although the modeling and control techniques applied are well known, the novelty of this work lies in its integration of experimental parameter identification, real-time validation, and practical hardware implementation within a unified and replicable framework. This approach provides a solid foundation for further studies involving more advanced or adaptive control strategies for BLDC motors. Full article

At present, the redundant structures are one of the most effective methods for solving magnetic levitation bearing coil failure. Coil failure causes residual effective magnetic poles to form different support structures and even asymmetrical structures. For the magnetic bearing with redundant structures, how to construct the electromagnetic force (EMF) that occurs under different support structures to achieve support reconstruction is the key to realizing fault tolerance control. To reveal the support reconstruction mechanism of magnetic bearing with a redundant structure, firstly, this paper takes a single-degree-of-freedom magnetic suspension body as an example to conduct a linearization theory analysis of the offset current, clarifying the concept of the current distribution matrix (CDM) and its function; then, the nonlinear EMF mode of magnetic bearing with an eight-pole is constructed, and it is linearized by using the theory of bias current linearization. Furthermore, the conditions of no coils fail, the 8th coil fails, and the 6–8th coils fail are considered, and, with the maximum principle function of EMF, the corresponding current matrices are obtained. Meanwhile, based on the CDM, the corresponding magnetic flux densities were calculated, proving that EMF reconstruction can be achieved under the three support structures. Finally, with the CDM and position control law, a fault-tolerant control system was constructed, and the simulation of the magnetic bearing with a redundant structure was carried out. The simulation results reveal the mechanism of support reconstruction with three aspects of rotor displacement, the value and direction of currents that occur in each coil. The simulation results show that, in the 8-pole magnetic bearing, this study can achieve support reconstruction in the case of faults in up to two coils. Under the three working conditions of wireless no coil failure, the 8th coil fails and the 6–8th coils fail, the current distribution strategy was adjusted through the CDM. The instantaneous displacement disturbance during the support reconstruction process was less than 0.28 μm, and the EMF after reconstruction was basically consistent with the expected value. Full article

Owing to its high energy efficiency, regenerative capability, and fast dynamic response, the Electromagnetic Energy-Feeding Shock Absorber has found widespread application in automotive suspension control systems. To further improve thrust control precision, this study presents a sliding mode thrust controller designed using an improved Gray Wolf Optimization algorithm. Firstly, an improved exponential reaching law is adopted, where a saturation function replaces the traditional sign function to enhance system tracking accuracy and stability. Meanwhile, a position update strategy from the particle swarm optimization (PSO) algorithm is integrated into the gray wolf optimizer (GWO) to improve the global search ability and the balance of local exploitation. Secondly, the improved GWO is combined with sliding mode control to achieve online optimization of controller parameters, ensuring system robustness while suppressing chattering. Finally, comparative analyses and simulation validations are conducted to verify the effectiveness of the proposed controller. Simulation results show that, under step input conditions, the improved GWO reduces the rise time from 0.0034 s to 0.002 s and the steady-state error from 0.4 N to 0.12 N. Under sinusoidal input, the average error is reduced from 0.26 N to 0.12 N. Under noise disturbance, the average deviation is reduced from 2.77 N to 2.14 N. These results demonstrate that the improved GWO not only provides excellent trajectory tracking and control accuracy but also exhibits strong robustness under varying operating conditions and random white noise disturbances. Full article