Induction machines sensors-less wind generator with integrated intelligent maximum power point tracking and electric losses minimisation technique

This study presents a high-performance wind generation system with induction machine (IM), specifically devised with the target of maximising the efficiency of the electromechanical conversion, and contemporary minimising the number of the system sensors and their cost. To this aim, the control system has been integrated, from one side, with an intelligent maximum power point tracking (MPPT) technique, so to make the generator track the power available in the wind, from the other side with techniques for the minimisation of the electrical losses (ELMT). Particularly, the power converters' switching losses have been reduced adopting a discontinuous pulsewidth modulation, while the IM overall losses have been reduced by a suitable electric losses minimisation technique. Contemporary, to reduce costs and increase the reliability of the system, the system has been devised as a fully sensors-less generation unit, meaning that both the wind speed and the machine speed sensors are not present. The anemometer has been substituted by the wind speed estimator integrated in the MPPT, based on the growing neural gas (GNG) network. The encoder has been substituted with an intelligent IM speed estimator, the so called MCA EXIN + reduced order observer (ROO). The performance of the adopted technique has been verified experimentally on a suitably devised test set-up

Jedan novi postupak estimacije brzine vrtnje vektorski upravljanog asinkronog motora zasnovan na adaptivnom sustavu s referentnim modelom i neuronskim mrežama

This paper proposes a new sensorless technique for induction motor drives based on a hybrid MRAS-neural technique, which improves a previously developed neural MRAS based sensorless method. In this paper the open-loop integration in the reference model is performed by an adaptive neural integrator, enhanced here by means of a speed-varying filter transfer function. The adaptive model is based on a more accurate discrete current model based on the modified Euler integration, with a resulting more stable behaviour in the field weakening region. The adaptive model is further trained on-line by a generalized least squares technique, the MCA EXIN + neuron, in which a parameterized learning algorithm is used. As a consequence, the speed estimation presents an improved convergence with higher accuracy and shorter settling time, because of the better transient behaviour of the neuron. A test bench has been set up to verify the methodology experimentally and the results prove its goodness at very low speeds (below 4 rad/s) and in zero-speed operation.U članku se predlaže novi postupak estimacije brzine vrtnje elektromotornog pogona s vektorski upravljanim asinkronim motorom. Postupak se zasniva na hibridnom adaptivnom sustavu s referentnim modelom (MRAS) i neuronskim mrežama. Takav postupak poboljšava prethodno razvijeni estimacijski postupak također zasnovan na »neuronskom MRAS-u«. U radu je realizirana integracija u otvorenoj petlji u referentnom modelu pomoću adaptivnog neuronskog integratora unaprijeđenog s filtrom čija prijenosna funkcija ovisi o brzini motora. Adaptivni je model zasnovan na točnijem diskretnom strujnom modelu motora dobivenom modificiranom Eulerovom integracijom, što rezultira stabilnijim vladanju pogona u režimu slabljenja polja. Adaptivni je model nadalje on-line obučavan korištenjem poopćene metode najmanjih kvadrata (»MCA EXIN+neuron« postupak) pri čemu se koristi parametrirani algoritam učenja. Zbog boljeg ponašanja neurona u dinamičkim stanjima poboljšava se konvergencija estimacije brzine s većom točnošću i manjim vremenom smirivanja. Za eksperimentalnu provjeru predložene metode izgrađena je laboratorijska maketa. Dobiveni rezultati potvrđuju valjanost metode na veoma niskim brzinama (ispod 4 rad/s) i u režimu nulte brzine

Jedan novi postupak estimacije brzine vrtnje vektorski upravljanog asinkronog motora zasnovan na adaptivnom sustavu s referentnim modelom i neuronskim mrežama

This paper proposes a new sensorless technique for induction motor drives based on a hybrid MRAS-neural technique, which improves a previously developed neural MRAS based sensorless method. In this paper the open-loop integration in the reference model is performed by an adaptive neural integrator, enhanced here by means of a speed-varying filter transfer function. The adaptive model is based on a more accurate discrete current model based on the modified Euler integration, with a resulting more stable behaviour in the field weakening region. The adaptive model is further trained on-line by a generalized least squares technique, the MCA EXIN + neuron, in which a parameterized learning algorithm is used. As a consequence, the speed estimation presents an improved convergence with higher accuracy and shorter settling time, because of the better transient behaviour of the neuron. A test bench has been set up to verify the methodology experimentally and the results prove its goodness at very low speeds (below 4 rad/s) and in zero-speed operation.U članku se predlaže novi postupak estimacije brzine vrtnje elektromotornog pogona s vektorski upravljanim asinkronim motorom. Postupak se zasniva na hibridnom adaptivnom sustavu s referentnim modelom (MRAS) i neuronskim mrežama. Takav postupak poboljšava prethodno razvijeni estimacijski postupak također zasnovan na »neuronskom MRAS-u«. U radu je realizirana integracija u otvorenoj petlji u referentnom modelu pomoću adaptivnog neuronskog integratora unaprijeđenog s filtrom čija prijenosna funkcija ovisi o brzini motora. Adaptivni je model zasnovan na točnijem diskretnom strujnom modelu motora dobivenom modificiranom Eulerovom integracijom, što rezultira stabilnijim vladanju pogona u režimu slabljenja polja. Adaptivni je model nadalje on-line obučavan korištenjem poopćene metode najmanjih kvadrata (»MCA EXIN+neuron« postupak) pri čemu se koristi parametrirani algoritam učenja. Zbog boljeg ponašanja neurona u dinamičkim stanjima poboljšava se konvergencija estimacije brzine s većom točnošću i manjim vremenom smirivanja. Za eksperimentalnu provjeru predložene metode izgrađena je laboratorijska maketa. Dobiveni rezultati potvrđuju valjanost metode na veoma niskim brzinama (ispod 4 rad/s) i u režimu nulte brzine

Design of a Fractional Order PI (FOPI) for the speed control of a high-performance electrical drive with induction motor

This paper describes the application of the Fractional Order PIs (FOPI) in the speed loop of a high performance induction motor electrical drive. In particular the speed tracking and load rejection capability of FOPI controller has been investigated and compared with both an integer-order PI and an IP both in simulation and experimentally with constant settling time. Illustrative study proves the simplicity and efficiency of the presented design method over integer controllers

Model Predictive Control for shunt active filters with fixed switching frequency

This paper presents a modification to the classical Model Predictive Control algorithm, named Modulated Model Predictive Control, and its application to active power filters. The proposed control is able to retain all the advantages of a Finite Control Set Model Predictive Control whilst improving the generated waveforms harmonic spectrum. In fact a modulation algorithm, based on the cost function ratio for different output vectors, is inherently included in the MPC. The cost function-based modulator is introduced and its effectiveness on reducing the current ripple is demonstrated. The presented solution provides an effective and straightforward single loop controller, maintaining an excellent dynamic performance despite the modulated output and it is self-synchronizing with the grid. This promising method is applied to the control of a Shunt Active Filter for harmonic content reduction through a reactive power compensation methodology. Significant results obtained by experimental testing are reported and commented, showing that MPC is a viable control solution for active filtering systems

Space-vector state dynamic model of SynRM considering self- and cross-saturation and related parameter identification

This study proposes a state formulation of the space-vector dynamic model of the Synchronous Reluctance Motor (SynRM) considering both saturation and cross-saturation effects. The proposed model adopts the stator currents as state variables and has been theoretically developed in both the rotor and stator reference frames. The proposed magnetic model is based on a flux versus current approach and relies on the knowledge of 11 parameters. Starting from the definition of a suitable co-energy variation function, new flux versus current functions have been initially developed, based on the hyperbolic functions and, consequently, the static and dynamic inductance versus current functions have been deduced. The dynamic inductance functions have been derived so to fulfill the reciprocity conditions. This study presents also a technique for the estimation of the parameters of the proposed magnetic model, which is based on stand-still tests without the need to lock the rotor. The identification process has been performed based on the minimization of a suitably defined error function including the difference between the measured and estimated stator fluxes. The proposed parameter estimation technique has been tested in both numerical simulation and experimentally on a suitably developed test set-up, permitting the experimental validation of the proposed model

Feedback Linearization Based Nonlinear Control of SynRM Drives Accounting for Self- and Cross-Saturation

This article proposes a nonlinear controller based on feedback linearization (FL) for synchronous reluctance motor (SynRM) drives which takes into consideration the magnetic saturation. The proposed nonlinear FL control based control technique has been developed starting from the theoretical definition of an original dynamic model of the SynRM taking into consideration both the self- and the cross-saturation effects. Such a control technique permits the dynamics of both the speed and axis flux loops to be maintained constant independently from the load and the saturation of the iron core in both constant flux and variable direct axis flux operating conditions. Finally, sensitivity of the performance of the proposed FL control versus the variation of the main motor parameters has been verified. The proposed technique has been tested experimentally on a suitably developed test setup. The proposed FL control has been further compared with the classic field-oriented control (FOC) in both constant flux and variable flux working conditions

Input-Output Feedback Linearization Control of a Linear Induction Motor Taking Into Consideration Its Dynamic End-Effects and Iron Losses

This article proposes a new input–output feedback linearization control (FLC) technique of linear induction motors (LIMs), taking into consideration both the dynamic end-effects and the iron losses. Starting from a previously conceived dynamic model, including the dynamic end-effects and the iron losses, all the theoretical framework of the FLC has been developed. The proposed FLC improves a previous version of FLC in accounting also the iron losses, which in LIMs with fixed-secondary sheet play a pivotal role more than in rotating induction motors (RIMs). The proposed FLC has been experimentally tested on a suitably developed test setup, and experimental comparisons between the proposed FLC, the classic field-oriented control and a previously developed FLC, not accounting for the iron losses, have been shown in variable flux working conditions

GA-Based Off-Line Parameter Estimation of the Induction Motor Model Including Magnetic Saturation and Iron Losses

This paper, starting from recent papers in the scientific literature dealing with Induction Motor (IM) dynamic modelling, as a first step, improves its space-vector dynamic model, including both the magnetic saturation and iron losses; particularly it takes into account the dependence of the magnetic saturation by the stator leakage inductance, as a further effect of the load. Afterwards, it proposes an off-line technique for the estimation of electrical parameters of this model, which is based on Genetic Algorithms (GA). The proposed method is based on input-output measurements and needs neither the machine design geometrical data nor a FEA of the machine. It focuses on the application of an algorithm based on the minimization of a suitable cost function depending on the stator current error. The proposed electrical parameters estimation method has been initially tested in numerical simulation and further verified experimentally on a suitably developed test set-up

A Qualitative Exploration of the Use of Contraband Cell Phones in Secured Facilities

Offenders accepting contraband cell phones in secured facilities violate state corrections law, and the possession of these cell phones is a form of risk taking behavior. When offenders continue this risky behavior, it affects their decision making in other domains where they are challenging authorities; and may impact the length of their incarceration. This qualitative phenomenological study examined the lived experience of ex-offenders who had contraband cell phones in secured correctional facilities in order to better understand their reasons for taking risks with contraband cell phones. The theoretical foundation for this study was Trimpop\u27s risk-homeostasis and risk-motivation theories that suggest an individual\u27s behaviors adapt to negotiate between perceived risk and desired risk in order to achieve satisfaction. The research question explored beliefs and perceptions of ex-offenders who chose to accept the risk of using contraband cell phones during their time in secured facilities. Data were collected anonymously through recorded telephone interviews with 8 male adult ex-offenders and analyzed using thematic content analysis. Findings indicated participants felt empowered by possession of cell phones in prison, and it was an acceptable risk to stay connected to family out of concern for loved ones. The study contributes to social change by providing those justice system administrators, and prison managers responsible for prison cell phone policies with more detailed information about the motivations and perspectives of offenders in respect to using contraband cell phones while imprisoned in secured facilities