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|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|7788||2012||5 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Applied Soft Computing, Volume 12, Issue 8, August 2012, Pages 2132–2136
This paper deals with the development of feed back controller design for a voltage controlled induction motor drive employing an enhanced optimization algorithm derived from the principles of foraging of natural ants. A linearized incremental model of a voltage controlled induction motor drive is shown to exhibit parameter variation at different operating points of the drive system. A PI-controller derived at a typical operating point using traditional methods does not give satisfactory performance for a wide bandwidth of load and reference speed changes. The newly developed Ant Colony Optimization technique enforces continuous exploration of the solution space and identifies optimal controller structure. The development of optimization algorithm and its application to feed back controller design for a variable voltage induction motor drive is well documented in this paper. Experimental and simulation results are presented to validate the efficacy of the optimized controller
The squirrel cage induction motor is basically a simple, less costly and reliable drive and can provide excellent characteristics at a constant shaft speed. Probably the cheapest and most reliable scheme of speed control of induction motor is stator voltage control using back-to-back connected SCRs. This scheme is widely used for certain types of loads such as fan and pump drives. It was shown that speed ranges of 5 to 1 can be easily obtained using this method ,  and . It may be noted that Induction motors are largely employed for Fan and pump drives in various industries as outlined in , , , , , ,  and . As a real data example, one may find the applications in Pulp and Paper industries , Cement industries ,  and , Refineries , etc. to name a few. AC voltage controller fed induction motors is also used for energy efficient operation ,  and . However, little attention is paid to the design of controller for closed loop operation using the above scheme. An experimental closed loop variable speed operation is described in . The drawback of  is that an analytical relationship could not be established between induction motor torque and applied voltage with thyristor excitation and only an empirical approach was used. Further, motor parameter variation with different operating points is not considered. In the recent days, ac voltage controllers are used for soft starting of induction motors and as energy savers ,  and . In this paper, an attempt has been made to develop an improved optimization technique based on Ant Colony Systems (ACS)  and  and is used for feedback controller design of stator voltage controlled induction motor drive. Each artificial ant is a complete solution to the problem at hand and is made to move towards increased pheromone traces. The movement of ant is probabilistically decided so as to simulate real ant movements. The optimization algorithm thus developed is employed for the feedback controller design of variable voltage induction motor drive system. The fifth order induction motor model is reduced to a first order linear incremental model and the effect of motor parameter variation on the speed response is analyzed. It is observed that, induction motor being a non-linear device, exhibits large parameter variation which requires online tuning of the controller parameters to achieve the best dynamic response at each operating point of the drive system. It is found from extensive simulation results that the proposed algorithm based on ant foraging identifies optimal controller parameters to achieve excellent dynamic response at all operating points.
نتیجه گیری انگلیسی
Induction motor is a non-linear device and its parameters vary with operating point. A simple transfer function model of the voltage controlled induction motor drive was derived from the fifth order d–q axis model of the machine and was used for simulation study. The application of ACS for determining the speed controller parameters is outlined in this paper. The problem is formulated as an optimization task and the control parameters are estimated. The speed response curve with the ACS tuned controller parameters gives an excellent response at all operating points compared to that of a conventional PI controller. Simulation and hardware results are presented to validate the claim.