Search Results (206)

Traditional low-order flux sliding mode observer (FSMO) and quadrature phase-locked loop (QPLL) structures generally encounter issues such as estimated signal chattering and inadequate dynamic performance. To overcome these challenges, this paper proposes an iterative fast super-twisting flux sliding mode observer (IFST-FSMO) and a tangent quadrature phase-locked loop (TQPLL) for sensorless control of surface-mounted permanent magnet synchronous motors (SPMSMs). Building on the traditional super-twisting algorithm (STA), the IFST-FSMO is proposed to accelerate convergence and enhance chattering suppression, which incorporates a linear term and utilizes the hyperbolic tangent function to replace the intrinsic sign function. Notably, the feedback matrix is redesigned to ensure the algorithm’s stability during speed reversal. Furthermore, an iterative calculation strategy is implemented under low-speed and light-load conditions, improving steady-state accuracy of estimated flux while avoiding increased computational burden at medium and high speeds. Regarding position estimation, a novel TQPLL with correction factor is proposed, utilizing the tangent function of the electrical angle error to achieve normalization and bandwidth adaptation. Ultimately, the proposed method is implemented on a motor test platform. Comparative experimental results demonstrate that the IFST-FSMO combined with TQPLL exhibits superior dynamic response and steady-state accuracy, while achieving efficient speed reversal. Full article

This paper proposes a model predictive control (MPC)-based approach for optimizing the performance of a photovoltaic (PV) system. The proposed method employs finite voltage-set maximum power point tracking (FVS-MPPT), ensuring precise duty cycle adjustment for a boost converter in the PV system considering the environmental changes in irradiation and temperature. Additionally, MPC is implemented for the grid-side converter to determine the optimal switching vector, ensuring precise control of active power via reference d-axis current and the elimination of reactive power by setting the reference q-axis current to zero. This approach optimizes the converter’s performance, maintaining a stable DC-link voltage while ensuring efficient grid integration. To ensure proper synchronization with the grid, a phase-locked loop (PLL) is utilized to provide the necessary grid voltage angle for dq frame transformation. Simulation results highlight the efficiency of the proposed MPC strategy, with the PV-side converter showing a robust response by dynamically adjusting the duty cycle to maintain optimal performance under varying irradiation and temperature conditions. Furthermore, the grid-side converter ensures precise control of active power and eliminates reactive power, enhancing the overall system’s stability and efficiency during grid interactions. A functional comparison of simulation results between the conventional P&O algorithm and the FVS-MPPT approach is presented, demonstrating the enhanced performance of the proposed technique over the conventional method including the total harmonic distortion for both techniques. Full article

This paper proposes a modification to existing saliency-based, sensorless control strategy for interior permanent magnet synchronous motors. The proposed approach leverages a two-interval, six-segment high-frequency voltage signal injection technique. It aims to improve rotor position and speed estimation accuracy when utilizing a single current sensor positioned in the inverter’s DC-bus circuit. The key innovation lies in modifying both the high-frequency signal injection and demodulation processes to address challenges in accurate phase current reconstruction and rotor position estimation, at low and zero speeds. A significant modification to the traditional high-frequency voltage signal injection method is introduced, which involves splitting the signal injection and the field-oriented control algorithm into two distinct sampling and switching periods. This approach ensures that no portion of the injected voltage space vector falls into the immeasurable region of space vector modulation, which could otherwise compromise current measurements. The dual-period structure, termed the two-interval six-segment high-frequency injection, allows for more precise current measurement during the signal injection period while maintaining optimal motor control during the field-oriented control period. Furthermore, this paper explores a different demodulation technique that improves the estimation of rotor position and speed. By employing a synchronous filter in combination with a phase-locked loop, the proposed method enhances the robustness of the system against noise and inaccuracies typically encountered in phase current reconstruction. The effectiveness of the proposed modifications is demonstrated through comprehensive simulation results. These results confirm that the enhanced method offers more reliable rotor position and speed estimates compared to the existing sensorless technique, making it particularly suitable for applications requiring high precision in motor control. Full article

Mixed Reality (MR) technology possesses profound and extensive potential across a multitude of domains, including, but not limited to industry, healthcare, and education. However, prolonged use of MR devices to watch stereoscopic content may lead to visual fatigue. Since visual fatigue involves multiple brain regions, our study aims to explore the topological characteristics of brain networks derived from electroencephalogram (EEG) data. Because the Phase-Locked Value (PLV) is capable of effectively measuring the phase synchronization relationship between brain regions, it was calculated between all pairs of channels in both comfort and fatigue states. Subsequently, a sparse brain network was constructed based on PLV by applying an appropriate threshold. The node properties (betweenness centrality, clustering coefficient, node efficiency) and edge properties (characteristic path length) were calculated based on the corresponding brain network within specific frequency bands for both comfort and fatigue states. In analyzing the PLV of brain connectivity in comfort and fatigue states, a notable enhancement in brain connectivity is observed within the alpha, theta, and delta frequency bands during fatigue status. By analyzing the node and edge properties of brain networks, it is evident that the mean values of these properties in the fatigue state were higher than those in the comfort state. By analyzing the node and edge properties at a local level, the average difference in betweenness centrality, clustering coefficients, and nodal efficiency across the three EEG frequency bands was computed to find significant brain regions. The main findings are as follows: Betweenness centrality primarily differs in frontal and parietal regions, with minor involvement in temporal and central regions. The clustering Coefficient mainly varies in the frontal region, with slight differences being seen in the temporal and occipital regions. Nodal efficiency primarily varies in the frontal, temporal, and central regions, with minor differences being seen in the parietal and occipital regions. Edge property analysis indicates that there is a higher occurrence of long-distance connections among brain regions during the fatigue state, which reflects a loss of synaptic transmission efficiency on a global level. Our study plays a crucial role in understanding the neural mechanisms underlying visual fatigue, potentially providing insights that could be applied to high-demand cognitive fields where prolonged use of MR devices leads to visual fatigue. Full article

An increase in renewable energy generation in the microgrid can cause voltage oscillation problems. To address this issue, an equivalent circuit of the microgrid was established, including a synchronous generator, grid-connected inverter, and constant power load. Then, the impact of different renewable energy generation ratios, different direct current (DC) voltage loops, and phase-locked loop control bandwidths of the grid-connected inverter on microgrid stability were analyzed. The results indicate that an increase in the renewable energy generation ratio leads to a decrease in the stability margin of the microgrid. A microgrid stability improvement method involving the parallel connection of a virtual resistor with the grid-connected inverter was proposed. The resistance value of the virtual resistor was obtained through an adaptive algorithm. This method ensures the stable operation of the microgrid under different renewable energy generation ratios. Full article

This work investigates the enhancement of optical energy in the synchronized dynamics of three erbium-doped fiber lasers (EDFLs) that are diffusively coupled in a unidirectional ring configuration without the need for external pump modulation. Before the system shows stable high-energy pulses, different dynamic behaviors can be observed in the dynamics of the coupled lasers. The evolution of the studied system was analyzed using different techniques for different values of coupling strength. The system shows the well-known dynamic behavior towards chaos at weak coupling, starting with a fixed point at low coupling and passing through Hopf and torus bifurcations as the coupling strength increases. An interesting finding emerged at high coupling strengths, where phase locking occurs between the frequencies of the three lasers of the system. This phase-locking leads to a significant increase in the peak energy of the EDFL pulses, effectively converting the emission into short, high amplitude pulses. With this method, it is possible to significantly increase the peak energy of the laser compared to a continuous EDFL single pulse. Full article

The high penetration of renewable energy sources (RESs) and power electronics devices has led to a continuous decline in power system stability. Due to the instability of grid-following converters (GFLCs) in weak grids, the grid-forming converters (GFMCs) have gained widespread attention featuring their flexible frequency and voltage regulation capabilities, as well as the satisfactory grid-supporting services, such as inertia and damping, et al. Notably, the risk of wideband oscillations in modern power grids is increasingly exacerbated by the reduced number of synchronous generators (SGs). Thus, the wideband oscillation suppression method based on adaptive active power droop control of GFMCs is presented in this paper. First, the stability of the hybrid grid-forming and grid-following system is obtained according to the improved short circuit ratio (ISCR), where the GFMC is in parallel at the point of common coupling (PCC) of the GFLC. Then, an adaptive adjustment strategy of the active power droop control is proposed to enhance the oscillation suppression capability across the full frequency range, thereby mitigating the wideband oscillation caused by phase-locked loop (PLL) synchronization in the GFLCs. Additionally, a first-order inertia control unit is added to the active and reactive power droop controllers to mitigate frequency and voltage variations as well as suppress potential mid-to-high frequency resonance. Finally, the wideband oscillation suppression strategy is validated by the simulation and experimental results. Full article

Hall sensors are commonly used to detect rotor position information in permanent magnet synchronous motors (PMSM). However, due to the low resolution of Hall sensors, the speed signal directly collected by the motor during rotation contains significant random errors and noise. Using this signal directly may increase the error and jitter in the rotor position estimation, thereby affecting the control performance of the system. This paper proposes a novel position estimation method that combines the Kalman filter and phase-locked loop (PLL) to precisely obtain the rotor position. In the proposed method, to suppress the noise and errors of the speed signal, the state and observation equations are established using the Kalman filter algorithm. Additionally, to enhance the precision of the rotor position estimation, the position obtained by integrating the speed from the Kalman filter is processed using the PLL algorithm, and the PLL algorithm parameters are dynamically corrected. To verify the feasibility and accuracy of the proposed speed and position estimation method, simulations and experiments are performed, respectively. By adopting the proposed method, the speed error is reduced by 30% to 50%, and the current harmonic component is reduced by about 48.7%, which effectively improves the accuracy of the rotor position estimation. Full article

When traditional grid-forming converters directly participate in the grid-connected operation of the power grid, due to the lack of a pre-synchronization control system, the voltage amplitude and initial phase on both sides of the grid-connected point will deviate, resulting in voltage and current distortion during grid-connected mode. An active support phase-locked loop free pre-synchronization control strategy based on the third-order model of a synchronous generator is proposed to address the grid-connected problem of the grid-forming converter mentioned above. First, a model of active support control with frequency integral feedback at small signal levels was constructed. The root locus method was employed to examine how system parameters affect the stability of the active support control system. Second, by adding phase pre-synchronization controllers and amplitude pre-synchronization controllers to the active frequency loop and excitation voltage loop of the third-order model, it was ensured that the frequency, phase, and voltage amplitude of the unit are consistent with the power grid, achieving a fast and smooth grid-connected mode of the unit. Finally, by using a DC source to simulate all types of new energy power generation equipment, the active support pre-synchronization control system based on the three-order model of synchronous generator is built in the MATLAB/Simulink simulation environment, and the accuracy and effectiveness of the control strategy in this paper is verified. Full article

In order to improve the observation accuracy of rotor positions in the sensorless control of permanent magnet synchronous motors and to simplify the parameter adjustment process, this paper proposes an improved finite-time adaptive super-twisting sliding mode observer. First, a linear gain term is introduced into the conventional super-twisting sliding mode observer model as a way of improving the identification accuracy of the observer. Then, for the multi-parameter variable problem in the traditional observer model, a rotational speed variable function design is presented, which simplifies the multi-variables into a single adaptive variable. This reduces the complexity of the observer model while further improving the observation accuracy and stability of the improved observer algorithm (which is verified using Lyapunov’s stability theory). A new back EMF filter and an adaptive phase-locked loop are then used to improve the model’s speed tracking capability. Finally, through simulation and experimental tests, the improved algorithm’s ability to quickly observe changes in rotor position and speed, as well as its fast convergence, small jitter and high accuracy characteristics, are verified. Full article

The current source inverter (CSI) has become the main grid-connected interface of distributed generation systems due to its advantages, such as boost capability, current controllability, and short-circuit protection capability. However, in weak grids, the grid-connected CSI that uses a phase-locked loop to achieve grid voltage synchronization has problems, such as instability in the fundamental positive-sequence voltage phase detection at the point of common coupling and instability in the current loop control, which seriously hamper the promotion and application of the CSI and its interconnected systems. For this reason, this paper proposes a sliding mode observer-based phase-locking strategy for the CSI. The strategy proposes a sliding mode observer for grid voltage phase detection, so that the grid current can directly follow the grid voltage, solving the problem of inconsistency or distortion between the voltage phase of the point of common coupling and the grid voltage phase in weak grids. On this basis, the grid impedance is regarded as part of the CL filter, and a robust parameter design method is proposed for the grid current closed-loop control in weak grids, which achieves robust operation of a CSI in weak grids. Finally, an experimental platform for a single-phase grid-connected CSI is built to verify the effectiveness and feasibility of the proposed scheme. Full article

Motivated by the operational scenarios of lock scheduling, we propose a serial-lock chain navigation problem (SLCNP) modeled on the Three Gorges-Gezhouba Dam (TGGD) for the first time. Ship grouping, synchronized moving, and grouped waiting operations are integrated into the ship navigation process. A mixed integer programming (MIP) model that incorporates real-world constraints such as ship priority, service fairness, traffic flow equilibrium, and phased ship placement is presented to optimize ship throughput and ship stay time. To solve the SLCNP, a sort-pick strategy-based swarm intelligence algorithm (SPSSIA) framework is developed that integrates the characteristics of SLCNP through a hybrid multi-section encoding method and a two-stage heuristic decoding approach. A swarm intelligence evolution mechanism is used to improve the search ability and robustness of the framework. Several instances are generated based on real data to verify the correctness and effectiveness of the model and algorithm. Computational results demonstrate the applicability and effectiveness of the proposed SPSSIA. Further analysis of the experimental results indicates that the key impact factors significantly influence the navigational performance of the TGGD system. The results of this study will provide practical guidance for the operational processes of inland river hubs with comparable characteristics. Full article

Monitoring the driver’s physical and mental state based on wearable EEG acquisition equipment, especially the detection and early warning of fatigue, is a key issue in the research of the brain–computer interface in human–machine intelligent fusion driving. Comparing and analyzing the waking (alert) state and fatigue state by simulating EEG data during simulated driving, this paper proposes a brain functional network construction method based on a phase locking value (PLV) and phase lag index (PLI), studies the relationship between brain regions, and quantitatively analyzes the network structure. The characteristic parameters of the brain functional network that have significant differences in fatigue status are screened out and constitute feature vectors, which are then combined with machine learning algorithms to complete classification and identification. The experimental results show that this method can effectively distinguish between alertness and fatigue states. The recognition accuracy rates of 52 subjects are all above 70%, with the highest recognition accuracy reaching 89.5%. Brain network topology analysis showed that the connectivity between brain regions was weakened under a fatigue state, especially under the PLV method, and the phase synchronization relationship between delta and theta frequency bands was significantly weakened. The research results provide a reference for understanding the interdependence of brain regions under fatigue conditions and the development of fatigue driving detection systems. Full article

As large-scale renewable energy sources are increasingly integrated into AC grids via voltage source converters (VSCs), the transient synchronization stability of phase-locked loop (PLL)-based VSCs during fault ride-through is gaining more attention. Most existing studies assume that the positive and negative sequence separation and current control dynamics are much faster than the PLL dynamics, thereby neglecting their impact on the transient synchronization stability of the system. However, when the PLL bandwidth is relatively large, ignoring the positive and negative sequence separation and current control dynamics may result in incorrect stability assessments. To address this issue, this paper first considers the multiple control loop coupling, including positive and negative sequence separation, current control, and PLL, to construct a full-order nonlinear mathematical model of the VSC grid-connected system under asymmetric fault conditions. Based on this, the phase trajectory method is employed to analyze the transient synchronization stability of the system. Additionally, this full-order mathematical model is used to determine the PLL bandwidth boundary beyond which the effects of positive and negative sequence separation and current control dynamics cannot be neglected. Finally, PSCAD/EMTDC simulation results validate the effectiveness of the theoretical analysis presented in this paper. Full article

This paper proposes a combined adaptive virtual Inertia and adaptive damping control of a virtual synchronous generator (AID-VSG) to improve the dynamic frequency response of microgrids. In the proposed control scheme, the VSG’s virtual inertia and damping coefficients adapt themselves during the transients to, respectively, reduce frequency deviations and increase the oscillations’ damping. In addition, as an important feature, the proposed AID-VSG is suitable for distributed control scheme applications and is designed to not rely on phase-locked loop (PLL) measurements, which avoids PLL stability issues on weak grids. The control parameters of the proposed AID-VSG are tuned by the particle swarm optimization (PSO) algorithm to minimize the overshoot and settling time of the microgrid’s frequency during an islanding event. The AID-VSG is validated by a comparative analysis with three existing VSG control schemes, also tuned by the stated optimization algorithm. The performance of each compared VSG strategy is evaluated through the simulation of a set of 10,000 initial conditions, using the islanded microgrid’s nonlinear model. The best response among the VSG strategies was achieved by the proposed AID-VSG control for both the optimization problem and the set of initial conditions’ simulations. Full article