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Modeling and Simulation of Speed of a Doubly Fed Induction Motor with Different Regulators
Many industrial applications require new control techniques in order to obtain fast response and to improve the dynamic performances. One of the techniques users, sliding mode,fuzzy logic and fuzzy sliding mode control which are characterizes by robustness and insensitivity to the parameters variation. In this paper, we present a comparative study of a direct stator flux orientation control of doubly fed induction motor by three regulators: sliding mode, fuzzy logic and fuzzy sliding mode. The three regulators are applies in speed regulation of doubly fed induction motor (DFIM). The robustness between these three regulators was tested and validated under simulations with the presence of variations of the parameters of the motor, in particular the face of disturbances of load torque. The results show that the three regulators are robust against external perturbations, but the fuzzy sliding mode controller has good performance than the fuzzy logic and sliding mode controllers.
Introduction
The doubly fed induction machine (DFIM) is a very attractive solution for variable-speed applications such as electric vehicles and electrical energy production. Obviously, the required variable-speed domain and the desired performance depends on the application. The use of a DFIM offers the opportunity to modulate power flow into and out the rotor winding. In general, when the rotor is fed through a eye locon verter, the power range can reach the order of megawatts - a level usually confined to synchronous machines [ I ].
The DFIM has some distinct advantages compared to the conventional squirrel-cage machine. The DFIM can be fed and controlled stator or rotor by various possible combinations. Indeed, the input-commands are done by means of four precise degrees of control freedom relatively to the squirrel cage induction machine where its control appears quite simpler. The flux orientation strategy can transform the non linear and coupled DFIM mathematical model to a linear model conducting to one attractive solution as well as under generating or motoring operations [2], Several methods of control are used to control the induction motor among which the vector control or field orientation control that allows a decoupling between the
torque and the flux, in order to obtain an independent control of torque and the flux like DC motors [3]. The overall performance of field-oriented-controlled induction motor drive systems is directly related to the performance of current control. Therefore, decoupling the control scheme is required by compensation of the coupling effect between q-axis and d-axis current dynamics [3]. With the field orientation control (FOC) method, induction machine drives are becoming a major candidate in high-performance motion control applications, where servo quality operation is required. Fast transient response is made possible by decoupled torque and flux control [4]. Sliding mode theory, stemmed from the variable
structure control family, has been used for the induction motor drive for a long time. It has for long been known for its capabilities in accounting for modelling imprecision and bounded disturbances. It achieves robust control by adding a discontinuous control signal across the sliding surface, satisfying the sliding condition. Nevertheless, this type of control has an essential drawback, which is the chattering phenomenon caused from the discontinuous control action. To alleviate the chattering phenomenon, the idea of boundary layer is used to improve it. It is called a modified controller. In this method, the control action was smoothed such that the chattering phenomenon can be decreased [5]. Fuzzy logic control is a technique of incorporating expert knowledge in designing a controller. Past research of universal approximation theorem shown that any nonlinear function over a compact set with arbitrary
accuracy can be approximated by a fuzzy system [9]. In the design of a fuzzy logic controller, the mathematical model is not necessary [6].Fuzzy logic has proven to be a potent tool in the
sliding mode control of time-invariant linear systems as well as time-varying nonlinear systems. It provides methods for formulating linguist rules from expert knowledge and is able to approximate any real continuous system to arbitrary accuracy. Thus, it offers a simple solution dealing with the wide range of the system parameters. All kinds of control schemes, including the classical sliding mode control, have been proposed in the field of AC machine control during the past decades [5]. Among these different proposed designs, the sliding
mode control strategy has shown robustness against motor parameter uncertainties and unmodelled dynamics, insensitivity to external load disturbance, stability and a fast dynamic response [7], [8], [9]. Hence it is found to be very effective in controlling electric drives systems. Large torque chattering at steady state may be considered as the main drawback for such a control scheme [7]. One way to improve sliding mode controller performance is
to combine it with Fuzzy Logic (FL) to form a Fuzzy Sliding Mode (FSM) controller [10].
In this paper, we treat direct stator flux orientation control (DSFOC) of doubly fed induction motor with three types of regulators, the fiizzy-PI, sliding mode and fuzzy sliding mode controllers.