Search Results (271)

This paper proposes an event-triggered extension of duty-ratio-based model predictive direct speed control (DR-MPDSC) for permanent magnet synchronous motor (PMSM) drives in electric vehicle (EV) applications. The main contribution is the development of an event-triggered execution framework specifically tailored to DR-MPDSC, in which control updates are performed only when the speed tracking error violates a prescribed condition, rather than at every sampling instant. Unlike conventional MPDSC and time-triggered DR-MPDSC schemes, the proposed strategy achieves a significant reduction in control execution frequency while preserving fast dynamic response and closed-loop stability. An optimized duty-ratio formulation is employed to regulate the effective application duration of the selected voltage vector within each sampling interval, resulting in reduced electromagnetic torque ripple and improved stator current quality. An extended Kalman filter (EKF) is integrated to estimate rotor speed and load torque, enabling disturbance-aware predictive speed control without mechanical torque sensing. Furthermore, a unified field-weakening strategy is incorporated to ensure wide-speed-range operation under constant power constraints, which is essential for EV traction systems. Simulation and experimental results demonstrate that the proposed event-triggered DR-MPDSC achieves steady-state speed errors below 0.5%, limits electromagnetic torque ripple to approximately 2.5%, and reduces stator current total harmonic distortion (THD) to 3.84%, compared with 5.8% obtained using conventional MPDSC. Moreover, the event-triggered mechanism reduces control update executions by up to 87.73% without degrading transient performance or field-weakening capability. These results confirm the effectiveness and practical viability of the proposed control strategy for high-performance PMSM drives in EV applications. Full article

The growing incorporation of distributed energy resources (DER) in power distribution grids, although pivotal to the energy transition, increases operational variability and amplifies the exposure to disturbances that can compromise resilience and the continuity of service during contingencies. Addressing these challenges requires both a shift toward flexible distribution architectures and the adoption of advanced power electronics interfacing systems. In this setting, this paper proposes a resilience-oriented strategy for medium-voltage (MV) distribution systems and clustered hybrid AC/DC microgrids interfaced through solid-state transformers (SSTs). When a fault occurs along an MV feeder segment, the affected microgrids naturally transition to islanded operation. However, once their local generation and storage become insufficient to sustain autonomous operation, the proposed framework reconfigures the power routing within the cluster by activating an emergency low-voltage DC (LVDC) power path that bypasses the faulted MV section. This mechanism enables controlled power sharing between microgrids during prolonged MV outages, ensuring the supply of priority loads without oversizing SSTs or reinforcing existing infrastructure. Experimental validation on a reduced-scale SST prototype demonstrates stable grid-forming and grid-following operation. The reliability of the proposed scheme is supported by both steady-state and transient experimental results, confirming accurate voltage regulation, balanced sinusoidal waveforms, and low current tracking errors. All tests were conducted at a switching frequency of 50 kHz, highlighting the robustness of the proposed architecture under dynamic operation. Full article

With the increasing integration of renewable energy into power grids, voltage source converter-based high-voltage direct current (VSC-HVDC) stations often adopt hybrid grid-following (GFL) and grid-forming (GFM) control strategies to improve adaptability to varying grid strengths. In many existing schemes, the hybrid coefficient changes abruptly, which may produce large transient current overshoots and compromise the safe and stable operation of converters. An adaptive hybrid GFL-GFM control framework equipped with a hybrid coefficient transition regulation is proposed. Small-signal state–space models are established and eigenvalue analysis confirms stability over the considered short-circuit ratio (SCR) range. The regulating method is activated only during coefficient transitions and is inactive in steady-state, thereby preserving the operating-point eigenvalue properties. Dynamic equations of the converter current change rate are derived to reveal the key role of the hybrid-coefficient change rate in driving transient current overshoots, based on which a real-time hybrid coefficient regulating method is developed to shape coefficient transitions. Simulations on a 500 kV/2100 MW VSC-HVDC project demonstrate reduced transient current overshoot and power oscillations during SCR variations, with robustness under moderate parameter deviations as well as representative SCR assessment error and update delay. Full article

To enhance the accuracy and timeliness of field testing for grounding impulse impedance in complex soil environments, this paper addresses the limitations of traditional peak-ratio methods—such as susceptibility to noise interference and the inability to reflect dynamic impedance variations—by proposing an identification method that combines an improved Hanning window with recursive least squares (RLS). During signal preprocessing, an improved Hanning window with adjustable parameters and energy normalization is employed to enhance the main-lobe energy concentration of impulse voltage and current signals while effectively suppressing high-frequency sidelobe leakage. In the parameter estimation stage, a low-order discrete linear model is established and an RLS algorithm with a forgetting factor is introduced to achieve full-time adaptive estimation of impulse impedance. Using a simulated surge test circuit, 18 sets of typical operating conditions with varying inductance and resistance parameters are designed. The same voltage and current data are processed using three processing methods: no windowing, standard Hanning windowing, and improved Hanning windowing. Results show that the average relative error of surge impedance is 9.16% without windowing, the standard Hanning window reduced the error to 3.78%, and the modified Hanning window further decreased the error to approximately 1.51%. Comparative analysis of different forgetting factor settings indicates that a value of approximately λ = 0.98 achieves an optimal trade-off between dynamic tracking capability and steady-state smoothness. The research results demonstrate that the proposed method achieves high identification accuracy for impact impedance and exhibits satisfactory parameter robustness under strong noise and multiple operating conditions, providing a reference for grounding impact characteristic testing and lightning protection design. Full article

In real life, almost all systems are nonlinear in nature. The electromagnetic levitation system (EMLS) is one such system that has a wide range of applications due to its frictionless, fast, and affordable technique. Optimal control and sliding mode control (SMC) techniques are often used controllers for EMLS. However, these techniques can achieve the required levitation but lag in having perfect set-point tracking and robustness against uncertainties. To get over these drawbacks, this article proposes the design of unconstrained mismatched uncertainties, constrained mismatched uncertainties, and integral sliding mode control with mismatched uncertainties for the current-controlled-type electromagnetic levitation system (CC-EMLS). The modeled equations of CC-EMLS are transfomed in terms of the mismatched uncertainties, and the required control action is obtained with and without constraints on the control input. The quadratic performance function is suggested for the unconstrained control scheme and is solved using the Hamilton–Jacobi–Bellman (HJB) equation. The non-quadratic cost function is designed for the constrained control method, and the HJB equation is utilized to obtain the solution. Both control schemes provide robustness to the system, but deviations in the set point are observed in tracking the position of the ball when the changes in the payload occur in the system. Therefore, integral sliding mode control with robust–optimal (IOSMC) gain is proposed for the CC-EMLS to overcome the steady-state error in the other two schemes. The stability is proven using the direct method of Lyapunov stability. The essential studies based on the simulation are carried out to showcase the performance of the proposed control schemes. The integral performance indicators are compared for all three proposed control schemes to highlight the efficacy, robustness, and efficiency of the designed controllers. Full article

Onboard models serve as the foundation for the advanced control and fault diagnosis of aero-engines. Currently, to address the issues of high computational complexity and insufficient real-time performance in component-level aero-engine models, three improvement methods are proposed: constructing the Jacobian matrix along the reverse flow path to avoid redundant calculations; reducing the number of initial guess variables and equations in the engine co-working system through aerothermodynamic analysis, thereby achieving dimensionality reduction in the nonlinear equation sets; and leveraging the minimal variation in Jacobian inverse elements across the full flight envelope to replace them with fixed gains, thus simplifying transient performance calculations. Simulation results demonstrate that, compared to the regular Newton-Raphson method, the reverse flow method reduces the steady-state, regular transient, and small-step transient calculation time by 27.6%, 33.9%, and 30.8%, respectively, with a maximum relative error within 1.6%; the dimensionality reduction method for equations cuts the steady-state, regular transient, and small-step transient calculation time by 20.1%, 11.4%, and 11.8%, with a maximum relative error within 1.4%; and the constant Jacobian matrix inverse method reduces the calculation time by 50.9% during full flight envelope transient performance simulation, with a maximum relative error below 1.6%. All methods improve real-time performance under rated operating conditions. However, only the reverse flow method preserves both high efficiency and accuracy under off-design operating conditions. Full article

The adoption of proton exchange membrane fuel cells (PEMFCs) in unmanned aerial vehicles (UAVs) offers a sustainable pathway to zero-emission propulsion, supporting aviation decarbonization by replacing battery or fossil fuel systems with efficient hydrogen technology. This work presents the development, validation, and application of a comprehensive dynamic model of a 1 kW open-cathode PEMFC system, including complete balance of plant (BOP) and control logic for four cooling fans, a purge valve, and a short-circuit unit (SCU). The model was validated through extensive experiments with step, triangular, and real-world UAV current profiles. Under steady-state conditions, it reproduces stack voltage with a <1 V average error and a temperature of 2.5 °C. Dynamic modeling accurately predicts fan behavior, purge/SCU events, and transient voltage drops. Applied to a 25 min UAV flight, the model quantifies reactant-management impacts: purge events increase H₂ usage by 4.8%, with SCU raising total to 5.6% above stoichiometric consumption. Altitude analysis shows ambient temperature reduction dominates the oxygen partial pressure effects, yielding net cell voltage increase under current-based fan control. These insights underscore explicit BOP and ambient modeling for accurate UAV endurance estimation and strategy optimization, providing a basis for future altitude-chamber validation. By enabling precise BOP dynamics simulation and H₂ optimization, this model advances the achievement of affordable clean energy, facilitating an extended endurance with minimal environmental impact. Full article

This study presents a comprehensive experimental investigation of a 2.2 kW brushless DC (BLDC) motor integrated with a three-shaft planetary gearbox, focusing on overall energy efficiency, battery state of charge (SOC) estimation, and real-time speed control under variable load conditions. In the first stage, the gearbox transmission ratio was experimentally verified to establish the kinematic relationship between the BLDC motor and the eddy current dynamometer shafts. In the second stage, the motor was operated in open loop mode at fixed reference speeds while variable load torques ranging from 1 to 7 N.m were applied using an AVL dynamometer. Electrical voltage, current, and rotational speed were measured in real time through precision transducers and a data acquisition interface, enabling computation of overall efficiency and SOC via the Coulomb counting method. The open loop results demonstrated that maximum efficiency occurred in the intermediate-to-high-speed region (2000 to 2800 rpm) and at higher load torques (5 to 7 N.m) while locking the third gearbox shaft produced negligible parasitic losses. In the third stage, a proportional–integral–derivative (PID) controller was implemented in closed loop configuration to regulate motor speed under the same variable load scenarios. The closed loop operation improved the overall efficiency by approximately 8–20 percentage points within the effective operating range of 1600–2500 rpm, reduced speed droop, and ensured precise tracking with minimal overshoot and steady-state error. The proposed methodology provides an integrated experimental framework for evaluating the dynamic performance, energy efficiency, and battery utilization of BLDC motor planetary gearbox systems, offering valuable insights for electric vehicle and hybrid electric vehicle (HEV) drive applications. Full article

In converter-dominated direct-current microgrids, severe load transients can cause large voltage deviations on the common direct-current bus. To mitigate this, an energy storage system is typically employed, and an isolated bidirectional dual active bridge converter is commonly used as the power interface. Therefore, the controller must ensure robust transient performance under step-load conditions. This paper proposes an active disturbance rejection control framework that adaptively adjusts the bandwidth of an extended state observer using fuzzy logic. The proposed observer increases its bandwidth during transients—based on the estimation error—to accelerate disturbance compensation, while decreasing the bandwidth near steady state to suppress noise amplification. This adaptive tuning alleviates the fixed-bandwidth trade-off between transient speed and noise sensitivity in ESO-based regulation. Hardware experiments under load-step conditions validate the method: for a load increase, the peak voltage undershoot and settling time are reduced by 22% and 48.9% relative to a proportional–integral controller, and by 20% and 36.1% relative to a fixed-bandwidth observer. For a load decrease, the peak overshoot and settling time are reduced by 27.9% and 49.5% compared with the proportional–integral controller, and by 20.5% and 25% compared with the fixed-bandwidth observer. Full article

Video satellites feature agile attitude maneuverability and the capability for continuous target imaging, making them an effective complement to ground-based remote sensing technologies. Existing research on video satellite tracking methods generally assumes either accurately calibrated camera parameters or precisely known target positions. However, deviations in camera parameters and errors in target localization can significantly degrade the performance of current tracking approaches. This paper proposes a novel adaptive visual tracking method for video satellites to track near-circular space targets in the presence of simultaneous uncertainties in both camera parameters and target position. First, the parameters representing these two types of uncertainties are separated through linearization. Then, based on the real-time image tracking error and the current parameter estimates, an update law for the uncertain parameters and a visual tracking law are designed. The stability of the closed-loop system and the convergence of the tracking error are rigorously proven. Finally, quantitative comparisons are conducted using a defined image stability index against two conventional tracking methods. Simulation results demonstrate that under coexisting uncertainties, traditional control methods either fail to track the target or exhibit significant tracking precision degradation. In contrast, the average image error during the steady-state phase exhibits a reduction of approximately one order of magnitude with the proposed method compared to the traditional image-based approach, demonstrating its superior tracking precision under complex uncertainty conditions. Full article

This study presents the development and experimental validation of a novel wind turbine emulator (WTE) based on a doubly fed induction generator (DFIG). The proposed architecture employs an induction motor (IM) driven by a variable frequency drive (VFD) to emulate wind turbine dynamics, offering a cost-effective and low-maintenance alternative to traditional DC motor-based systems. The contribution of this work lies, therefore, not in the hardware topology itself, but in the complete real-time software implementation of the control system using C language and RTLib, which enables higher sampling rates, faster PWM updates, and improved execution reliability compared with standard Simulink/RTI approaches. The proposed control structure integrates tip–speed ratio (TSR)-based maximum power point tracking (MPPT) with flux-oriented vector control of the DFIG, fully coded in C to provide optimized real-time performance. Experimental results confirm the emulator’s ability to accurately replicate real wind turbine behavior under varying wind conditions. The test bench demonstrates fast dynamic response, with rotor currents settling in 11–18 ms, and active/reactive powers stabilizing within 25–30 ms. Overshoots remain below 10%, and steady-state errors are limited to ±1 A for currents and ±100 W/±50 VAR for powers, ensuring precise power regulation. The speed tracking error is approximately 0.61 rad/s, validating the system’s ability to follow dynamic references with high accuracy. Additionally, effective decoupling between active and reactive loops is achieved, with minimal cross-coupling during step changes. Full article

This paper presents a physically constrained grey-box identification framework for electromechanical systems, illustrated through the dynamics of brushed DC motors. The method estimates all electromechanical parameters by minimizing a normalized residual that combines current, velocity, and steady-state algebraic constraints under a current-limit condition. Classical approaches such as least-squares and black-box identification often lack physical interpretability and do not explicitly enforce steady-state consistency, making their estimates susceptible to nonphysical parameter drift. The proposed formulation incorporates these physical constraints within a Levenberg–Marquardt scheme with signal normalization, enabling the joint minimization of current and velocity errors. Validation was performed using step-response data from two DC motors under both synthetic and experimental conditions. When applied to unfiltered measurements, the method maintained steady-state relative errors below 1% and achieved low trajectory discrepancies, with NRMSE in velocity between 2.6 and 3.2% and NRMSE in current between 0.9 and 1.2% across both motors. Embedding physical and steady-state constraints directly into the cost function improves robustness and ensures physically consistent parameter estimates, even under high measurement noise and without filtering. The approach provides a general strategy for dynamic system identification under physical consistency requirements and is suitable for rapid calibration, diagnostic monitoring, and controller tuning in robotic and mechatronic applications. Full article

With increasing wind power penetration in modern grids, high-performance current control of converters is essential for efficient power transfer, harmonic reduction, and system stability. A novel discrete switching sequence control (dSSC) is proposed to ensure power converters universally track current references without steady-state error. A discrete model of the H-bridge converter is developed, together with a detailed, systematic design methodology to realize the dSSC. The resulting controller is applicable to arbitrary current references and guarantees zero steady-state error. Compared with pulse width modulation (PWM), the dSSC accounts for converter switching characteristics and provides a systematic design framework for both dynamic performance and steady-state accuracy. Moreover, the average switching frequency is approximately half that of PWM, which reduces maintenance and improves converter efficiency in wind-turbine applications. Simulation and experimental results validate the proposed method. Full article

To address the vibration issues in bearingless interior permanent magnet synchronous motors (BIPMSMs) caused by rotor mass unbalance and inverter dead-time (DT) effects during operation, a vibration suppression strategy based on a Proportional–Integral–Resonant (PIR) controller is proposed. Firstly, the mathematical model of the BIPMSM is established, and the principle of suspension force generation is analyzed. Secondly, the mechanism underlying rotor vibration is theoretically investigated. Thirdly, a PIR controller is designed by connecting a modified Proportional–Resonant (PR) controller in parallel with a Proportional–Integral (PI) controller. The proposed controller combines the ideal PR controller’s characteristic of achieving infinite gain at the resonant frequency, enabling zero steady-state error tracking for sinusoidal signals at the resonant frequency. Finally, a vibration suppression system based on the PIR controller is constructed, and simulation experiments are conducted for verification. The simulation results show that the PIR controller effectively reduces both rotor mass unbalance vibration and DT vibration in the BIPMSM, while also suppressing current harmonics during the motor’s operation. Full article

This paper presents an improved sliding-mode observer (SMO) for estimating mechanical parameters and compensating load torque in permanent magnet synchronous motor (PMSM) drives. Traditional SMOs have limited robustness when the motor model is inaccurate. To solve this, an enhanced sliding-mode observer (ESMO) is proposed. It can estimate both the total inertia and the load torque at the same time. The method is verified using Lyapunov stability analysis and convergence time calculation. Experimental results show that, when combined with a single-vector Model Predictive Current Control (MPCC), the proposed ESMO achieves zero overshoot during no-load startup and keeps the steady-state error below 0.1% under load changes. It also reduces q-axis current ripple and improves harmonic suppression. This control method is suitable for applications that require high precision and strong robustness, such as robots, electric vehicles, and smart manufacturing. Full article