5 research outputs found

    Sensorless Control of Induction Motors by the MSA based MUSIC Technique

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    This paper proposes a speed sensorless technique for induction motor drives based on the retrieval and tracking of the rotor slot harmonics (RSH). The RSH related to the rotor speed is first extracted from the stator phase current signature by the adoption of two cascaded ADALINEs (ADAptive Linear Element), whose output is the estimated slot harmonic. Then, the frequency of this slot harmonic as well as the speed is estimated by using minor space analysis (MSA) EXIN neural networks, which work on-line to iteratively compute the frequency of the slot harmonics based on MUSIC spectrum estimation theory. Thanks to its sample-based learning and the reduced mean square frequency estimation error, the speed estimation is fast and accurate. The proposed sensorless technique has been experimentally tested on a suitably developed test set-up with a 2-kW induction motor drive. It has been verified that this algorithm can track the rotor speed rapidly and accurately in a very wide speed range, working from rated speed down to 1.3 % of it

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

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    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

    Innovative Observers for Induction Motor Control

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    In this thesis the problem of designing observers and controllers for induction motors has been studied and thoroughly discussed using tools from the nonlinear system theory, both for analysis and control purposes. Useful techniques have been used to identify the machine parameters off-line. In the Introduction was dealt the design a control system for a drive of asynchronous machines that uses a voltage source inverter to generate the currents and voltages which carry the drive by making use of an observer of the state rotor variables. The used control algorithms is the \textit{field oriented control} (FOC). The model of the asynchronous induction motor is described starting from the mechanical model, the electrical model through the Steinmetz equivalent electrical circuit that is the IEEE recommended equivalent circuit, the State Model of Asynchronous Motor and the mathematical model, completing with the discretization of the last model, realizing the Discrete time mathematical model. In Chapter 1 several observer are taken in account in order to be able to compare their strengths and weaknesses. At first it's developed a (FOLO) Full Order Luemberger Observer and its Reduced Order version. Other observer that was considered it's the Sliding one. Then a version of Non linear Flux observer was synthesized in order to consider the effects of saturation which introduce a nonlinear effects. At last the (EKF) Extended Kalman Filter was considered, both in complex (ECKF) and the (RAKF) Robust Adaptive Kalman Filter version. In Chapter 2 have been presented experimental and simulation results obtained by testing each of the previous algorithms. Excellent results were obtained by use of observer based on Kalman Filter, and in particular, the Extended Complex Kalman Filter, because no matrix inversion is required. In fact the operation of matrix inversion that is necessary in the classic Extended Kalman Filter is therefore translated in the inverse of a real number in the proposed Extended Complex Kalman Filter. In conclusion, a set of tools present in control theory have been applied successfully in motion control systems with induction motors. This work is certainly not a complete treatment, since many basic parts are omitted (only the references are given), and for this reasons is to be understood as completion of studies related to the subject matter
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