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In this paper an adaptive minimum variance controller is proposed to minimize the rate of stochastic inputs from uncontrollable high priority sources. This method avoids the computations needed for pole placement design of the minimum variance controller, and utilizes an online recursive least squares algorithm in direct tuning of the controller parameters.
In spite of improvement of AC drive systems, still DC drivers are widely used in industry. One of the problems which might cause unsuccessful attempts for designing a proper controller would be the time-varying nature of parameters and variables which might be changed while working with the motion systems. One of the best suggested solutions to solve this(More)
implementation of fixed and variable frequency ADALINE schemes for grid connected VSI synchronization " , in proc. A centroid-based PWM switching technique for full bridge inverter applications " , Random pulse width modulation techniques for converter-fed drive systems–A review " , Design of an FPGA based real-time simulator for electrical system " , in(More)
This paper presents development of a neuro-fuzzy system for performance enhancement of a.c.voltage controller fed induction motor drives. Improvement in motor efficiency and power factor is achieved by suitably adapting the motor flux to optimum point by stator voltage control. The optimum SCR firing angle for each operating point is readily estimated by(More)
Induction motor is the electrical drives which are widely used in major industrial applications. Generally efficiency of the induction motor is poor at lower load condition. It is necessary to improve the efficiency for the better performance that is possible with the modeling of an induction motor. In this work the mathematical model of an Induction Motor(More)
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