Speed Sensorless Vector Control of Induction Motors Based on Robust Adaptive Variable
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12-10-2010, 10:39 AM

This article is presented by:
O. Barambones∗, A.J. Garrido∗, F.J. Maseda∗ and P. Alkorta†
Speed Sensorless Vector Control of Induction Motors Based on
Robust Adaptive Variable Structure Control Law

A novel sensorless adaptive robust control law is proposed to improve the trajectory tracking performance of induction motors. The proposed design employs the so called vector (or field oriented) control theory for the induction motor drives and the designed control law is based on an integral slidingmode algorithm that overcomes the system uncertainties. The proposed sliding-mode control law incorporates an adaptive switching gain to avoid calculating an upper limit of the system uncertainties. The proposed design also includes a new method in order to estimate the rotor speed. In this method, the rotor speed estimation error is presented as a first order simple function based on the difference between the real stator currents and the estimated stator currents. The stability analysis of the proposed controller under parameter uncertainties and load disturbances is provided using the Lyapunov stability theory. Finally simulated results show, on the one hand that the proposed controller with the proposed rotor speed estimator provides high-performance dynamic characteristics, and on the other hand that this scheme is robust with respect to plant parameter variations and external load disturbances.
Field oriented control method is widely used for advanced control of induction motor drives. By providing decoupling of torque and flux control demands, the vector control can govern an induction motor drive similar to a separate excited direct current motor without sacrificing the quality of the dynamic performance. However, the field oriented control of induction motor drives presents two main problems that have been providing quite a bit research interest in the last decade. The first one relies on the uncertainties in the machine models and load torque, and the second one is the precise computation of the motor speed without using speed sensors. The decoupling characteristics of the vector control is sensitive to machine parameters variations. Moreover, the machine parameters and load characteristics are not exactly known, and may vary during motor operations. Thus the dynamic characteristics of such systems are very complex and nonlinear. Therefore, many studies have been made on the motor drives in order to preserve the performance under these parameter variations and external load disturbances, such as nonlinear control, optimal control, variable structure system control, adaptive control and neural control [7], [8], [11], [12], [13]. To overcome the above system uncertainties, the variable structure control strategy using the sliding-mode has been focussed on many studies and research for the control of the AC servo drive system in the past decade [2], [3], [6], [14], [17]. The sliding-mode control can offer many good properties, such as good performance against unmodelled dynamics, insensitivity to parameter variations, external disturbance rejection and fast dynamic response [20]. These advantages of the slidingmode control may be employed in the position and speed control of an AC servo system. However the traditional sliding control schemes requires the prior knowledge of an upper bound for the system uncertainties since this bound is employed in the switching gain calculation. This upper bound should be determined as precisely as possible, because as higher is the upper bound higher value should be considered for the sliding gain, and therefore the control effort will also be high, which is undesirable in a practice. In order to surmount this drawback, in the present paper it is proposed an adaptive law to calculate the sliding gain which avoids the necessity of calculate an upper bound of the system uncertainties. Otherwise, a suitable speed control of an induction motor requires a precise speed information, therefore, a speed sensor, such a resolver and encoder, is usually adhered to the shaft of the motor to measure the motor speed. However, a speed sensor can not be mounted in some cases, such as motor drives in a adverse environments, or high-speed motor drives. Moreover, such sensors lower the system reliability and require special attention to noise. Therefore, sensorless induction motor drives are widely used in industry for their reliability and flexibility, particularly in hostile environments. Speed estimation methods using Model Reference Adaptive System MRAS are the most commonly used as they are easy to design and implement [4], [10], [21]. However, the performance of these methods is deteriorated at low speed because of the increment of nonlinear characteristics [9], [15].

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20-02-2012, 04:53 PM

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