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The purpose of this paper is to obtain an accurate methodology for modelling and analysis of the permanent magnet synchronous generator connected to power electronic components.

This paper presents the methodology of the co-simulation of a permanent magnet synchronous generator. It combines Simulink, Maxwell and Simplorer software to demonstrate the electrical machine behaviour connected with the power electronics’ circuit. The finite element analysis performed on the designed machine exhibit a more accurate behaviour over simplified Simulink models. Results between both simulation and co-simulation are compared to measurements.

The co-simulation approach offers a more accurate depiction of the machine behaviour and its interaction with the non-linear circuits.

This paper focuses on the interior permanent magnet type of PMSG and its interaction with a passive rectifier (nonlinear circuit).

The advanced capabilities of the co-simulation method allow to analyse more variations (geometry, materials, etc.), and its interaction with non-linear circuits, than previous simulation techniques.

The co-simulation as a tool for analysis and design of systems interconnected with unconventional and conventional electrical machines and prototypes, and the comparison of the obtained results with classical analysis and design methods, against measurements obtained from the prototype.

This paper aims to obtain an accurate and robust estimation method of the rotor flux and speed for the sensorless induction motor (IM) drive.

The reduced order observer has been used as an online tuned rotor flux model in the model reference adaptive system (MRAS) concept applied for the IM speed estimation. The output of this observer was used also as a feedback signal required in the direct field‐oriented control (DFOC) structure of the IM.

It is shown that a new rotor flux and speed estimator are more robust to motor parameter changes in comparison with the classical MRAS estimator and can work stably in the DFOC structure, in the wide speed range, even for relatively high (50 per cent) identification errors of equivalent circuit parameters of the IM.

The investigation looked mainly at the estimation accuracy performance and whole system stability while economic issues will still need to be addressed.

The proposed new improved MRAS speed estimator can be easily realised using modern digital signal processors. The implementation was tested in an experimental set‐up with floating point DSP used as the system controller. The fixed‐point realisation needs to be developed to obtain the practical application in the industrial drive systems.

The application of the reduced order flux observer as a tuned flux model in the MRAS type speed estimator instead of the simple, but very sensitive to motor parameter uncertainties, current flux model, enables much better accuracy and stability of the rotor speed estimation in the complex DFOC structure than in the case of classical MRAS estimator.

The purpose of this paper is to obtain an accurate and robust estimation method of the rotor flux and speed for the sensorless induction motor (IM) drive with magnetizing reactance variations.

The sensorless IM drive with sliding mode flux and speed observer (SMO) is presented. Proposed estimation algorithm is extended with the additional magnetizing reactance estimator based on the magnetizing characteristic of the IM. The dynamical and steady‐state properties of the drive system in the low‐speed and in the field‐weakening regions are tested. The simulation results are verified by experimental tests, over the wide range of motor speed and drive parameter changes.

It is shown that the sensorless induction motor drive can work stable in wide speed range using the Sliding‐Mode Observer with additional magnetizing reactance estimator.

The investigation looked mainly at the speed estimation methodology with additional motor parameter estimator.

The proposed SMO can be easily implemented on digital signal processors. The implementation was tested in an experimental setup with DS1103 card. The fixed‐point realisation needs to be developed to obtain the practical application in the industrial drive systems.

The SMO with an additional magnetizing reactance estimator based on magnetizing characteristic of the IM is tested. This method of the speed and flux reconstruction can be applied in different electrical drives working in wide speed range, including very low‐speed region and field‐weakening region, too. The proposed solution is not sensitive to magnetizing reactance variations and is simple in practical implementation in the real‐time system.

Various control structures and approaches are in use nowadays. Development of new ideas allows to obtain better quality in control of different industrial processes and hence better quality of products. As it may seem that everything in the classical systems has already been discovered, more and more research centres are tending to incorporate fuzzy or neural control systems. The purpose of this paper is to present an application of the adaptive neuro-fuzzy PID speed controller for a DC drive system with a complex nonlinear mechanical part.

The model of the driven object including such elements as nonlinear shaft with backlash and friction has been modelled using Matlab-Simulink software. Afterwards experimental verification has been made using a dSPACE control card and experimental system with two DC motors connected with an elastic shaft.

The presented study shown that the adaptive controller is able to damp the torsional vibration effectively even for the wide range of the system nonlinearities. What is more the design approach for controllers design parameters has been described. Proposed approach is based on requested properties of system. Using proposed tuning scheme no detailed information about the object are needed.

This paper presents for the first time fully an PID adaptive neuro-fuzzy controller. The inputs are the weighted tracking error, error’s derivative and integrated error. What is more the adaptation algorithm consists of a model tracking error its derivative and integer. Also the proposed tuning algorithm in such a form is an original outcome.

This study aims to develop a finite element method based co-simulation platform for the numerical analysis of motor drive system. With the rising requirement of industry, the comprehensive design of motor drive systems has attracted increasing attentions. An accurate model, which considers the coupling between motor and its drive system, is vital for the analysis and design of motor drive system.

Considering the coupling relationship between motor and its drive system, a flexible and extensible co-simulation platform of motor drive system is developed with the C++ language and finite element machine model to carry out the comprehensive analysis of motor drive system. The control system simulation program developed with C++ language adopts the same discrete form as the single-chip microcomputer and can simulate the interrupt mechanism, making the simulation closer to the actual control system. With the finite element analysis results of current step, the winding input voltage of next step is calculated by the executable program of control system and is fed into the finite element analysis, forming the two-way coupling analysis of drive system.

Preliminary studies, such as calculation of machine core losses fed by inverters, and control parameters optimization, are conducted with this platform, which shows the flexibility and expansibility of this platform.

The power inverter circuit along with the controller is modeled using the C++ language, and embedded into the finite element machine model to achieve more realistic motor drive system simulation and complex functions.

The purpose of this paper is analysis of the sensorless control system of induction machine with broken rotor for diagnostic purposes. Increasing popularity of sensorless controlled variable speed drives requires research in area of reliability, range of stable operation, fault symptoms and application of diagnosis methods.

T transformation used for conversion of instantaneous rotor currents electrical circuit representation to space vector components is investigated to apply with closed‐loop modeling algorithm. Evaluation of the algorithm is based on analysis of asymmetry influence to the orthogonal and zero components of space vector representation. Multiscalar model of the machine and selected structures of state observers are used for sensorless control system synthesis. Proposed method of frequency characteristics calculation is used for state observers analysis in open‐loop operation.

New algorithm of applying the T transformation allows for closed‐loop and sensorless control system simulation with asymmetric machine due to broken rotor. Compensating effect of the closed‐loop control system with speed measurements and diagnosis information in control system variables are identified. Proposed frequency analysis of state observers is presented and applied. Variables with amplified characteristic frequency components related to rotor asymmetry are compared for selected structures of state observers and with closed‐loop and open‐loop operation. Method of improving the sensorless system stability is proposed.

In closed‐loop and sensorless control system rotor fault can be diagnosed by using PI output controllers variables. Compensating effect of mechanical variables sets limitation to specified diagnosis methods. Rotor asymmetry affects sensorless control system stability depending on estimator structure.

This paper concentrates upon sensorless control system operation with machine asymmetry and indicates rotor fault symptoms.

This paper presents a comparative study of different stator-segmentation topologies of a permanent magnet synchronous machine (PMSM) used in traction drives and their effect on iron losses. Using stator segmentation allows one to achieve more significant copper fill factors, resulting in increased power densities and efficiencies. The segmentation of the stators creates additional air gaps and changes the soft magnetic material’s material properties due to the cut edge effect. The aim of this paper is to present an in-depth analysis of the influence of stator segmentation on iron losses. The main goal was to compare various segmentation methods under equal excitation conditions in terms of their influence on iron loss.

A transient finite element method analysis combined with an extended iron-loss model was used to evaluate discussed effects on the stator’s iron losses. The workflow to obtain a homogenized airgap length accounting for cut edge effects was established.

The paper concludes that the segmentation in most cases slightly decreases the iron losses in the stator because of the overall reduced magnetic flux density B due to the additional air gaps in the magnetic circuit. An increase of the individual components, as well as total power loss, was observed in the Pole Chain segmentation design. In general, segmentation did not change the total iron losses significantly. However, different segmentation methods resulted in the different distortion of the magnetic field and, consequently, in different iron loss compositions. The analysed segmentation methods exhibited different iron loss behaviour with respect to the operation points of the machine. The final finding is that analysed stator segmentations had a negligible influence on the total iron loss. Therefore, applying segmentation is an adequate measure to improve PMSMs as it enables, e.g. increase of the winding fill factor or simplifying the assembly processes, etc.

The influence of stator segmentation on iron losses was analysed. An in-depth evaluation was performed to determine how the discussed changes influence the individual iron loss components. A workflow was developed to achieve a computationally cheap homogenized model.

The purpose of this paper is to improve the performance of sensorless vector control of induction motor drives by developing a new sliding mode observer for rotor speed and fluxes estimation from measured stator currents and voltages and estimated stator currents.

In the present paper, the discontinuity in the sliding mode observer is smoothed inside a thin boundary layer using fuzzy logic techniques instead of sign function to reduce efficiently the chattering phenomenon that affects the rotor speed.

The feasibility of the proposed fuzzy sliding mode observer has been verified by experimentation. The experimental results are obtained with a 1 kW induction motor using a dSPACE system with DS1104 controller board showing clearly the effectiveness of the proposed approach in terms of dynamic performance compared to the classical sliding mode observer.

The experimental results of the whole control structure highlights that this kind of sensorless induction motor drive can be used for variable speed drive in industrial applications such as oil drilling, electric vehicles, high speed trains (HSTs) and conveyers. Such drives may work properly at zero and low speed in both directions of rotation.

Both the proposed speed observer and the classical sliding mode observer have been developed and implemented experimentally with other adaptive observers for detailed comparison under different operating conditions, such as parameter variation, no-load/load disturbances and speed variations in different speed operation regions.

This paper aims to propose a novel system identification and resonance suppression strategy for motor-driven system with high-order flexible manipulator.

In this paper, first, a unified mathematical model is proposed to describe both the flexible joints and the flexible link system. Then to suppress the resonance brought by the system flexibility, a model based high-order notch filter controller is proposed. To get the true value of the parameters of the high-order flexible manipulator system, a fuzzy-Kalman filter-based two-step system identification algorithm is proposed.

Compared to the traditional system identification algorithm, the proposed two-step system identification algorithm can accurately identify the unknown parameters of the high order flexible manipulator system with high dynamic response. The performance of the two-step system identification algorithm and the model-based high-order notch filter is verified via simulation and experimental results.

The proposed system identification method can identify the system parameters with both high accuracy and high dynamic response. With the proposed system identification and model-based controller, the positioning accuracy of the flexible manipulator can be greatly improved.

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.