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The purpose of this paper is to describe a new method for selective harmonic elimination in a two-level three-phase inverter-fed direct torque controlled (DTC) permanent magnet synchronous motor (PMSM) drive to suppress unwanted resonant frequencies.

The design methodology is based on random space vector pulse-width modulation (RSVPWM) of PMSM drives. MATLAB simulations support the validity of suggested structure.

The simulation results of the proposed algorithm exhibit the development of a proper gap at the selected frequency in the frequency spectra of the motor input currents and voltages as well as lowering the ripples in the PMSM electromagnetic torque, stator current and flux linkage responses in compared with traditional DTC.

The proposed algorithm is a revised form of the RSVPWM technique used in a closed-loop structure along with a sliding mode speed controller which is capable to deal with nonlinear motor loads in an online manner. This study can be beneficial for the designers of AC motor drive system who attempt to find a modulation method that can create a selective gap in the power spectrum density of the motor input voltages and currents, therefore, promote an acoustically pleasant drive or alleviate unwanted motor vibrations.

The purpose of this paper aims to design a robust wind turbine emulator (WTE) based on a three-phase induction motor (3PIM).

The 3PIM is driven by a soft voltage source inverter (VSI) controlled by a specific space vector modulation. By adjusting the appropriate vector sequence selection, the desired VSI output voltage allows a real wind turbine speed emulation in the laboratory, taking into account the wind profile, static and dynamic behaviors and parametric variations for theoretical and then experimental analysis. A Mexican hat profile and a sinusoidal profile are therefore used as the wind speed system input to highlight the electrical, mechanical and electromagnetic system response.

The simulation results, based on relative error data, show that the proposed reactive power control method effectively estimates the flux and the rotor time constant, thus ensuring an accurate trajectory tracking of the wind speed for the wind emulation application.

The proposed architecture achieves its results through the use of mathematical theory and WTE topology combine with an online adaptive estimator and Lyapunov stability adaptation control methods. These approaches are particularly relevant for low-cost or low-power alternative current (AC) motor drives in the field of renewable energy emulation. It has the advantage of eliminating the need for expensive and unreliable position transducers, thereby increasing the emulator drive life. A comparative analysis was also carried out to highlight the online adaptive estimator fast response time and accuracy.

The direct torque control (DTC) of induction motor (IM) drive is featured by high ripples in the electromagnetic torque and stator flux profiles because they are controlled by two hysteresis regulators. Furthermore, the machine flux is not directly measurable. Hence, it is better to reconstitute it from the instantaneous electrical equations of the machine. Once the stator flux is estimated, we can guarantee a reliable sensorless DTC control. Thus, the purpose of this research work is to ensure fast response and full reference tracking of the IM under sensorless DTC strategy with desired dynamic behavior and low ripple levels.

In this work, an improved DTC strategy, which is DTC_SVM_3L, is suggested. The first step of the designed approach is to substitute the conventional inverter feeding the motor with a three-level inverter because it guarantees reduced switching losses, improved quality of voltage waveform and low-current total harmonic distortion rate. The second aim of this paper is to make the IM operate at a constant switching frequency by using the nearest three vectors-based space vector modulation (SVM) technique rather than hysteresis controllers. The third objective of this study is to conceive a sliding-mode stator flux observer, which can improve the control performances by using a sensorless algorithm to get an accurate estimation, and consequently, increase the reliability of the system and decrease the cost of using sensors. The stability of the proposed observer is demonstrated based on the Lyapunov theory. To overcome the load change disturbance in the proposed DTC control strategy, this paper exhibits a comparative assessment of four speed regulation methods: classical proportional and integral (PI) regulator, fuzzy logic PI controller, particle swarm optimization PI controller and backstepping regulator. The entire control algorithm was tested under different disturbances such as stator resistance and load torque variations.

It was ascertained that the IM, controlled with three-level inverter, exhibits good performances under the proposed DTC-SVM strategy based on a sliding-mode observer. The robustness of the suggested approach against parameter variations is also proved.

The theoretical development of the proposed control strategy is thoroughly described. Then, simulations using Matlab/Simulink software are launched to investigate the merits of the sensorless DTC-SVM command of three-level inverter-fed IM drive with different speed regulators.

The purpose of this paper is to develop a hybrid algorithm using differential evolution (DE) and prediction error modeling (PEM) for identification of small-scale autonomous helicopter state-space model.

In this study, flight data were collected and analyzed; MATLAB-based system identification algorithm was developed using DE and PEM; parameterized state-space model parameters were estimated using the developed algorithm and model dynamic analysis.

The proposed hybrid algorithm improves the performance of the PEM algorithm in the identification of an autonomous helicopter model. It gives better results when compared with conventional PEM algorithm inside MATLAB toolboxes.

This study is applicable to only linearized state-space model.

The identification algorithm is expected to facilitate the required model development for model-based control design for autonomous helicopter development.

This study presents a novel hybrid algorithm for system identification of an autonomous helicopter model.

Four‐quadrant AC‐DC converters are one kind of the most common and popular AC‐DC converters, which are serious EMI sources. The purpose of this paper is to propose a novel control for four‐quadrant AC‐DC converters to suppress the generated electromagnetic interference (EMI).

A chaotic carrier plays an important role to implement the chaotic PWM control. The relationship between the EMI distribution and carrier frequency is given by deducing and analyzing the harmonic components of the AC‐DC converter. The comparison of chaotic PWM control and random PWM control in suppressing EMI are provided.

The simulation results prove the effectiveness of the proposed chaotic PWM control on EMI reduction.

The effects of EMI suppression under different chaotic carriers will be theoretically analyzed in the future work.

The proposed chaotic PWM control can suppress EMI for converters without adding additional devices or components, therefore, without increasing the volume, weight and cost of converters.

In this paper, a novel chaotic pulse width modulation (PWM) control is proposed and implemented into a four‐quadrant AC‐DC converter for electromagnetic interference (EMI) suppression, moreover, the total harmonic distortion (THD) of the input AC current is also improved under chaotic PWM control.

The knowledge of power network parameters (which are usually unknown or poorly quantified and cannot be measured directly) is very valuable for power system modelling, simulation, protection and control; since it is fundamental for solving many problems such as minimizing the effect of voltage distortion, active filter control or relay setting. The purpose of this paper is to develop a new, easy, effective and reliable method for power network parameters identification.

The proposed identification method is based on current transient injections performed by a pulse width modulated power converter (which can be a rectifier or an active filter already installed in the network) and the analysis of the resultant network voltage response at the point of common coupling using genetic algorithms optimization.

Simulation tests show the effectiveness of the proposed identification strategy achieving negligible errors, even in practical conditions when measurement noise is included. It is also a very flexible method since the optimization routine can be updated or modified in order to improve the performance.

The developed method is non‐invasive, and uses only hardware already present on the power system, identifying the single parameters rather than the total impedance. It will provide improvements to several areas of power quality control. For example, when used within a stand‐alone piece of instrumentation, it will be possible to build up mesh equivalent networks of unknown power and distribution systems, which can then be used for load flow studies, protection or harmonic penetration prediction.

This study aims to provide a new method of multiscale directional Lyapunov exponents (MSDLE) calculated based on the state space reconstruction for the nonstationary time series, which can be applied to detect the small target covered by sea clutter.

Reconstructed state space is divided into non-overlapping submatrices whose columns are equal to a predetermined scale. The authors compute eigenvalues and eigenvectors of the covariance matrix of each submatrix and extract the principal components σ_ip and their corresponding eigenvectors. Then, the angles ψ_ip of eigenvectors between two successive submatrices were calculated. The curves of (σ_ip, ψ_ip) reflect the nonlinear dynamics both in kinetic and directional and form a spectrum with multiscale. The fluctuations of (σ_ip, ψ_ip), which are sensitive to the differences of backscatter between sea wave and target, are taken out as the features for the target detection.

The proposed method can reflect the local dynamics of sea clutter and the small target within sea clutter is easily detected. The test on the ice multiparameter imaging X-ban radar data and the comparison to K distribution based method illustrate the effectiveness of the proposed method.

The detection of a small target in sea clutter is a compelling issue, as the conventional statistical models cannot well describe the sea clutter on a larger timescale, and the methods based on statistics usually require the stationary sea clutter. It has been proven that sea clutter is nonlinear, nonstationary or cyclostationary and chaotic. The new method of MSDLE proposed in the paper can effectively and efficiently detect the small target covered by sea clutter, which can be also introduced and applied to military, aerospace and maritime fields.

The purpose of this paper is to suggest a novel current sensor-less drive system for a novel axial flux-switching permanent-magnet motor drive to reduce the costs and avoid problems caused by faults of the current sensors.

Commonly, a conventional controller needs at least two current sensors; in this paper, the current sensors are removed by replacing estimated stator current with the extended Kalman filter.

A prototype of the novel axial flux-switching permanent-magnet motor is fabricated and tested. It is found that the experimental results confirm the proposed method and show that the control has almost the same performance and ability as the conventional control.

The axial flux-switching permanent-magnet motor is one of the most efficient motors, but current sensor-less control of an axial flux-switching permanent-magnet motor with a sandwiched permanent magnet and a unity displacement winding factor has not been specially reported to date. Thus, in this paper, the authors report on current sensor-less control based on the extended Kalman filter for electric vehicles.

This paper aims to investigate the performance of two novel direct torque control (DTC) schemes dedicated to three-switch three-phase inverter (B3-VSI), also called delta inverter, fed induction motor (IM) drives.

The principle of operation of the B3-VSI-fed IM drive is recalled in a first step. Then, the basis of both proposed DTC strategies is presented. The first DTC scheme considers a subdivision of the stationary plane into three sectors and the application of the intrinsic as well as virtual voltage vectors to achieve the control combinations. While, the second DTC scheme considers a subdivision of the stationary plane into six sectors and a limitation of the voltage vectors incorporated in the look-up table to the three intrinsic ones.

Simulation and experimental results have revealed that, under steady-state operation and transient conditions, the harmonic content of the IM stator phase currents is lower in the case of the DTC2 strategy, resulting in a lower ripple of electromagnetic torque. Furthermore, it has led to a quasi-circular shape of the locus described by the stator flux vector in the stationary plane.

This work should be extended to the synthesis and performance analysis of a new DTC strategy for B3-VSI-fed IM drive, which emulates the operation of the conventional six-switch three-phase inverter-fed IM drive.

The limitation associated with the reduced number of the intrinsic voltage vectors generated by the B3-VSI has been eradicated, thanks to the suitable synthesis of the look-up table incorporated in the DTC scheme.

This paper aims to propose an improved direct torque control (DTC) for the induction motor’s performance enhancement using dual nonlinear techniques. The exact feedback linearization is implemented to create a linear decoupled control. Besides, the fuzzy logic control approach has been inserted to generate the auxiliary control input for the feedback linearization controller.

To improve the DTC for induction motor drive, this work suggests the incorporation of two nonlinear approaches. As the classical feedback linearization suffers while the presence of uncertainties and modeling inaccuracy, it is recommended to be associated to another robust control approach to compensate the uncertainties of the model and make a robust control versus the variations of the machine parameters. Therefore, fuzzy logic controllers will be integrated as auxiliary inputs to the feedback linearization control law.

The simulation and the experimental validation of the proposed control algorithm show that the association of dual techniques can effectively achieve high dynamic behavior and improve the robustness against parameters variation and external disturbances. Moreover, the space vector modulation is used to preserve a fixed switching frequency, reduce ripples and low switching losses.

The theoretical, simulation and experimental studies prove that the proposed control algorithm can be used on different AC machines for variable speed drive applications such as oil drilling, traction systems and wind energy conversion systems.

The proposed DTC strategy has been developed theoretically and realized through simulation and experimental implementation. Different operation conditions have been conducted to check the ability and robustness of the control strategy, such as steady state, speed reversal maneuver, low-speed operation and parameters variation test with load application.