Search Results (313)

LiDAR-assisted wind turbine control holds strong potential for reducing structural loads and improving rotor speed regulation, thereby contributing to more sustainable wind energy generation. However, key research gaps remain: (i) the practical limitations of commercially available fixed beam LiDARs for large turbines, and (ii) the performance assessment of commonly used LiDAR assisted feedforward control methods. This study addresses these gaps by (i) analysing how the coherence of LiDAR estimated rotor effective wind speed is influenced by the number of beams, measurement locations, and turbulence box resolution, and (ii) comparing two established control strategies. Numerical simulations show that applying a low cut-off frequency in the low-pass filter can impair preview time compensation. This is particularly critical for large turbines, where reduced coherence due to fewer beams undermines the effectiveness of LiDAR assisted control compared to the smaller turbines. The subsequent evaluation of control strategies shows that the Schlipf method offers greater robustness and consistent load reduction, regardless of the feedback control design. In contrast, the Bossanyi method, which uses the current blade pitch measurements, performs well when paired with carefully tuned baseline controllers. However, using the actual pitch angle in the feedforward pitch rate calculation can lead to increased excitation at certain frequencies, particularly if the feedback controller is not well tuned to avoid dynamics in those ranges. Full article

The radial magnetic bearing system is an open-loop, unstable, strong nonlinear system with a high rotor speed, predisposition to jitter, and poor interference immunity. The system is subjected to the main interference generated by gravity, and rotor imbalance and sensor runout seriously affect the system’s rotor position control performance. A plug-in repetitive control method based on equivalent-input-disturbance (EID) is presented to address the issue of decreased control accuracy of the magnetic bearing system caused by disturbances from gravity, rotor imbalance, and sensor runout. First, a linearized model of the magnetic bearing rotor containing parameter fluctuations due to the eddy current effect and temperature rise effect is established, and a plug-in repetitive controller (PRC) is designed to enhance the rejection effect of periodic disturbances. Next, an EID system is introduced, and a Luenberger observer is used to estimate the state variables and disturbances of the system. The estimates of the EID are then used for feedforward compensation to address the issue of large overshoot in the system. Finally, simulations are conducted for comparison with the PID control method and PRC control method. The plug-in repetitive controller method assessed in this paper improves control performance by an average of 87.9% and 57.7% and reduces the amount of over-shooting by an average of 66.5% under various classes of disturbances, which proves the efficiency of the control method combining a plug-in repetitive controller with the EID theory. Full article

This paper presents a novel adaptive twisting sliding mode control strategy combined with a speed-sensorless cascade nonlinear observer for the high-performance control of linear induction motors (LIMs). The primary objective is to achieve accurate speed and rotor flux tracking without relying on mechanical sensors, thereby enhancing system reliability and reducing hardware complexity. For this purpose, a cascade nonlinear observer is designed and applied to the class of nonlinear affine systems representing LIM dynamics. Based on the interconnected form of the LIM mathematical model, the observer simultaneously reconstructs both the motor speed and rotor fluxes in real time. The stability of the proposed cascade observer is analyzed using Lyapunov theory, ensuring the convergence of the estimation errors under bounded disturbances. Complementing the observer, two adaptive gain twisting sliding mode controllers are developed: one for speed tracking and another for flux regulation. These controllers are robust against external disturbances and parameter uncertainties, even when the bounds of such disturbances are unknown. This feature significantly enhances the practical applicability of the control system in real-world industrial environments. To validate the performance and robustness of the proposed control scheme, a hardware-in-the-loop (HIL) experiment was conducted. Comparative studies with existing state-of-the-art sensorless control methods demonstrate that the proposed cascade nonlinear observer-based approach achieves faster convergence, higher estimation accuracy, and better disturbance rejection capabilities, while requiring less computational effort. Full article

With the increasing capacity of wind turbines, key components including the rotor diameter, tower height, and tower radius expand correspondingly. This heightened inertia extends the response time of pitch actuators during rapid wind speed variations occurring above the rated wind speed. Consequently, wind turbines encounter significant output power oscillations and complex structural loading challenges. To address these issues, this paper proposes a novel pitch control strategy combining an effective wind speed estimation with the inverse system method. The developed control system aims to stabilize the power output and rotational speed despite wind speed fluctuations. Central to this approach is the estimation of the aerodynamic rotor torque using an extended Kalman filter (EKF) applied to the drive train model. The estimated torque is then utilized to compute the effective wind speed at the rotor plane via a differential method. Leveraging this wind speed estimate, the inverse system technique transforms the nonlinear wind turbine dynamics into a linearized, decoupled pseudo-linear system. This linearization facilitates the design of a more agile pitch controller. Simulation outcomes demonstrate that the proposed strategy markedly enhances the pitch response speed, diminishes output power oscillations, and alleviates structural loads, notably at the tower base. These improvements bolster operational safety and stability under the above-rated wind speed conditions. Full article

High-frequency (HF) injection is a widely used technique for low-speed implementation of position sensorless permanent magnet synchronous motor control. A key component of this technique is the tracking loop control system, which extracts rotor position error and utilizes proportional–integral regulation as a position observer for estimating the rotor position. Generally, this process relies on band-pass filters (BPFs) and low-pass filters (LPFs) to modulate signals in the quadrature current to obtain rotor position error information. However, limitations in filter accuracy and dynamic response lead to prolonged convergence times and timing inconsistencies in the estimation process, which affects real-time motor control performance. To address these issues, this study proposes an exponential moving average (EMA)-based scheme for rotor position error extraction, offering a rapid response under dynamic conditions such as direction reversals, step speed changes, and varying loads. EMA is used to pass the original rotor position information carried by the quadrature current signal, which contains HF components, with a specified smoothing factor. Then, after the synchronous demodulation process, EMA is employed to extract rotor position error information for the position observer to estimate the rotor position. Due to its computational simplicity and fast response in handling dynamic conditions, the proposed method can serve as an alternative to BPF and LPF, which are commonly used for rotor position information extraction, while also reducing computational burden and improving performance. Finally, to demonstrate its feasibility and effectiveness in improving rotor position estimation accuracy, the proposed system is experimentally validated by comparing it with a conventional system. Full article

To enhance the robustness of sensorless control in permanent magnet synchronous motors (PMSMs) under parameter mismatches, this paper proposes a novel sliding mode observer (SMO) that automatically adjusts the error factor. The purpose is to enable the precise observation of rotor position in PMSMs while simultaneously suppressing chattering and simplifying the design process. First, an SMO based on an adjustable error factor is designed, which reduces chattering and eliminates the need for a low-pass filter (LPF). The impact of the error factor within the SMO is then analyzed, including its effects on the estimation of current, speed, and position, and a method for determining the error factor based on these estimated values is introduced. This method uses a neural network algorithm to balance chattering suppression with high control accuracy. Finally, a neural network-based self-adjusting SMO model is proposed to automatically adjust the error factor based on motor operating conditions. Simulation and experimental results demonstrate the feasibility and effectiveness of this approach. Full article

This study presents a detailed investigation of the torque-speed characteristics of a WEG single-phase squirrel-cage induction motor (SPSCIM) of (1/2 hp), 110/220 V at 60 Hz. The primary objective was to derive the motor’s equivalent circuit and validate its performance curves through finite element analysis (FEA), simulation using MATLAB^®/Simulink^®, and experimental testing. Finite element simulations were conducted using the software FEMM (Finite Element Method Magnetics) to model the magnetic flux distribution within the motor’s stator and rotor. These simulations, based on the motor’s dimensions and nameplate data, provided essential insights into the electromagnetic behavior, including flux density and saturation effects, which are crucial for accurate torque-speed curve predictions. For experimental validation, tests were performed under open-circuit and locked-rotor conditions through a universal machine as a load emulator. The torque-speed characteristics were determined using the Suhr method and the classical approach, with the resulting curves compared to experimental measurements. Voltage and current were measured using AC PZEM-004T and DC PZEM-017 meters, while rotor speed was monitored with a Hall effect sensor (A3144). The results revealed strong agreement between the FEM simulations, Surh method, and experimental data, demonstrating the reliability and accuracy of the combined simulation and analytical methods for modeling the motor’s performance. The estimations using classical and Suhr methods, Simulink simulations, and FEMM yielded low error percentages, mostly below 2%. However, in the FEMM simulation, rotor resistance showed a higher error of around 20% due to unavailable data on the exact number of windings turns, a modifiable parameter that can be corrected through further adjustments in the simulation. The torque-speed curves obtained at different voltage levels showed an excellent correlation, confirming the effectiveness of the proposed approach in characterizing the motor’s operational behavior. Full article

Achieving excellent speed control in permanent magnet synchronous motors (PMSMs) relies on the simultaneous suppression of both aperiodic and periodic disturbances. This paper presents an enhanced Active Disturbance Rejection Control (ADRC) strategy specifically designed to address these disturbances in single-rotor compressors (SRCs). To achieve simultaneous suppression, a Recursive Gauss–Newton (RGN) algorithm is implemented in parallel with the conventional extended state observer (ESO) to enhance the ADRC framework. The RGN algorithm iteratively estimates the amplitude and phase information of periodic disturbances, while the ESO primarily observes the system’s aperiodic disturbances. In contrast to existing methods, the proposed angle-based approach demonstrates superior performance during speed transients. Detailed convergence and decoupling analyses are provided to facilitate parameter tuning. The effectiveness of the proposed method is validated through simulations and experiments conducted on a 650 W SRC, demonstrating its superiority over proportional–integral (PI) control, conventional ADRC, and quasi-resonant controller-based ADRC (QRC-ADRC) under both steady-state and dynamic conditions. Full article

The twin propeller system can be powered by a motor with dual-rotating rotors, which generally necessitates that both rotors run at the same speed to prevent rolling. The motor with dual-rotating rotors is popular for applications that benefit from high torque density and an axially compact form factor. In order to minimize the effects of load disturbances and internal parameter perturbations on the motor performance, this paper proposes a control strategy combining disturbance observer and sliding mode control (SMC) technologies to realize the purpose of both rotors rotating at the same speed. There are issues with the conventional proportional-integral (PI) control for load disturbances and motor parameter variations, whereas the SMC method has its invariant properties. Meanwhile, the system disturbances obtained by a disturbance observer are estimated to be used as feed-forward compensation for the SMC control in order to reduce the undesired chattering during the SMC control process. The validity and practicability of the control strategies proposed in this paper are demonstrated by both simulations and experiments. Full article

High-frequency injection (HFI) is widely adopted for the sensorless control of permanent magnet synchronous motors (PMSMs) at low speeds. However, conventional HFI strategies relying on fixed-frequency carrier modulation and square-wave injection concentrate current harmonic energy within narrow spectral bands, thereby inducing pronounced high-frequency motor vibrations and noise. To mitigate this issue, this paper proposes a noise suppression strategy based on synchronized periodic frequency modulation (PFM) of both the carrier and high-frequency square-wave signals. By innovatively synchronizing the periodic modulation of the triangular carrier in space vector pulse width modulation (SVPWM) with the injected high-frequency square wave, harmonic energy dispersion and noise reduction are achieved, substantially lowering peak acoustic emissions. First, the harmonic characteristics of the voltage-source inverter output under symmetric triangular carrier SVPWM are analyzed within a sawtooth-wave PFM framework. Concurrently, a harmonic current model is developed for the high-frequency square-wave injection method, enabling the precise derivation of harmonic components. A frequency-synchronized modulation strategy between the carrier and injection signals is proposed, with a rigorous analysis of its harmonic suppression mechanism. The rotor position is then estimated via high-frequency signal extraction and a normalized phase-locked loop (PLL). Comparative simulations and experiments confirm significant noise peak attenuation compared to conventional methods, while position estimation accuracy remains unaffected. This work provides both theoretical and practical advancements for noise-sensitive sensorless motor control applications. Full article

Precise speed estimation of sensorless induction motor (SIM) drives remains a significant challenge, particularly at zero and very low speeds. This paper proposes a mathematically modeled and enhanced stator current-based Model Reference Adaptive System (MRAS) estimator integrated with correction terms using rotor flux dynamics to continually update the value of the estimated speed to the correct value. The MRAS observer uses the stator current in the adjustable IM model instead of the rotor flux or the back emf to eliminate the effect of pure integration of the rotor flux, the parameters’ deviation, and measurement errors of stator voltages and currents on speed observation. It depends on the observed stator current, the current estimate error, and rotor flux estimation correction terms. A neural network (NN) for the adaptive law of the MRAS observer is proposed to enhance the accuracy of the suggested approach. Simulation results examine the developed method. A laboratory prototype based on DSP-DS1103 was also built, and the experimental results are presented. The SIM drive is examined at zero and very low speeds in motoring and regenerating modes. It exhibits good dynamic performance and low-speed estimation error compared to the conventional MRAS. Full article

To address the issues of poor stability and susceptibility to external disturbances in traditional model reference adaptive systems (MRASs) for permanent magnet synchronous motors (PMSMs), this paper proposes a sliding mode control strategy based on an improved model reference adaptive observer. First, the dynamic equations of the PMSM are used as the reference model, while the stator current equations incorporating speed variables are constructed as the adjustable model. Subsequently, a novel adaptive law is designed using Popov’s hyperstability theory to enhance the estimation accuracy of rotor position. A fractional-order system was introduced to construct both a fractional-order sliding surface and reaching law. Subsequently, a comparative study was conducted between the conventional integral terminal sliding surface and the proposed novel sliding mode reaching law. The results demonstrate that the new reaching law can adaptively adjust the switching gain based on system state variables. Under sudden load increases, the improved system achieves a 25% reduction in settling time compared to conventional sliding mode control (SMC), along with a 44% decrease in maximum speed fluctuation and a 42% reduction in maximum torque ripple, significantly enhancing dynamic response performance. Furthermore, a variable-gain terminal sliding mode controller is derived, and the stability of the closed-loop control system is rigorously proven using Lyapunov theory. Finally, simulations verify the effectiveness and feasibility of the proposed control strategy in improving system robustness and disturbance rejection capability. Full article

In this study, a sensorless vector control method was proposed for a doubly fed induction machine (DFIM), where the stator is directly connected to the grid. The DFIM is a three-phase symmetric system without saliency, and when the stator side is directly connected to the grid, the magnitude and frequency of the stator flux are almost fixed and determined by the grid voltage. Due to its three-phase symmetric configuration, this structure can be modeled in a manner similar to that of a symmetric permanent-magnet synchronous motor (PMSM). It enables the application of back-EMF-based sensorless control methods commonly used for symmetric PMSMs. In PMSMs, sensorless estimators typically estimate the back-EMF using only stator voltage and current measurements. By extending this modeling concept to DFIMs, a similar estimator can be designed that utilizes only rotor-side voltage and current for sensorless back-EMF estimation. This paper proposes a back-EMF estimator using only rotor-side voltages and currents, which were implemented on a stator flux reference frame. The proposed algorithm also estimates the stator-side variables, including the magnitudes of stator voltage, current, and stator power factor. These variables can be used to detect grid faults. The feasibility of the proposed method was validated via experiments using a 2.4 kW DFIM. It was confirmed that the sensorless operation functioned properly even during speed acceleration/deceleration and step load conditions. Additionally, the system maintained stable operation and achieved an accurate estimation of stator voltage and current, even under a 30% voltage sag in the stator grid voltage. Full article

A permanent magnet synchronous motor (PMSM) is typically run at low speed with a sensorless control system using a high-frequency signal injection method. However, current harmonic and gain errors compromise rotor position observation accuracy. In this paper, we analyze the reasons for rotor observation angle error and propose a new rotor position observer with error compensation. This new sensorless control tool obtains the compensation error angle by extracting the negative high-frequency current in order to estimate the rotor position information accurately. The experimental results show that the error compensation strategy proposed in this paper can improve the accuracy of rotor position observation and achieve operation of the PMSM in both steady-state working conditions and dynamic working conditions at low speed. Full article

In the context of the new energy hybrid ship propulsion system (NE-HSPS), the parameters of the rotor speed, torque, and current of the permanent magnet synchronous motor (PMSM) are susceptible to environmental variations and unmodeled disturbances. Conventional nonlinear controllers (e.g., backstepping, PI, and sliding mode) encounter challenges related to response speed, interference immunity, and vibration jitter. These challenges stem from the inherent uncertainties in perturbations and the limitations of the traditional nonlinear controllers. In this paper, a novel Adaptive Finite-Time Command-Filtered Backstepping Controller (AFTCFBC) is proposed, featuring a faster response time and the elimination of overshoot. The proposed controller is a significant advancement in the field, addressing the computational complexity of backstepping control and reducing the maximum steady-state error of the control output. The novel controller incorporates a Nonlinear Finite-Time Command Filter (NFTCF) adapted to the variation in motor speed. Secondly, a novel Nonlinear Sliding Mode Observer (NSMO) is proposed based on the designed nonlinear sliding mode gain function (φ(S_w)) to estimate the load disturbance of the electric propulsion system. The Uncertainty Parameter-Adaptive law (UPAL) is designed based on Lyapunov theory to improve the robust performance of the system. The construction of a simulation model of a hybrid ship PMSM under four distinct working conditions, including constant speed and constant torque, the lifting and lowering of speed, loading and unloading, and white noise interference, is presented. The results of this study demonstrate a significant reduction in speed-tracking overshoot to zero, a substantial decrease in integral squared error by 90.15%, and a notable improvement in response time by 18.6%. Full article