scholarly journals DRNN Robust DTC for Induction Motor Drive Systems Using FSTPI

2021 ◽  
Vol 54 (4) ◽  
pp. 539-547
Author(s):  
Lucky Dube ◽  
Ehab H.E. Bayoumi

In this paper, a self-tuning PI speed controller based on diagonal recurrent neural network is (DRNN) investigated and simulated to increase the robustness of the direct torque control (DTC) scheme for three-phase low-power IM drive system using a Four Switch Three-Phase Inverter (FSTPI). The drive is subjected to different system inputs and disturbances, step changes in speed under different load conditions, abrupt loading at high speed and speed reversal. Furthermore, the robustness of the controller is evaluated by varying motor parameter, stator resistance and moment of inertia. A comparison of classical and self-tuning PI speed controllers was presented to determine the effectiveness of the proposed controller. It is concluded based on simulation results using Matlab/Simulink. that the self-tuning PI speed controller provides the best performance by reacting rapidly and adaptively.

2019 ◽  
Vol 11 (3) ◽  
pp. 293-308
Author(s):  
Rawaa Kadhim Sakran ◽  
Assist. Prof. Dr. Khearia Mohammed Ali

This paper deals with the performance analysis of three phase Induction Motor (IM) with Direct Torque Control based Space Vector Modulation (DTC-SVM). The DTC-SVM scheme is a kind of high-performance control of IM drives to improve the ripples of torque and flux in steady state, which one drawback of conventional DTC. DTC-SVM has three Proportional-Integral (PI) controllers, one used as the PI speed controller and other PI flux controller and PI torque controller, which are utilized to produce the stator voltage references (


2010 ◽  
Vol 6 (2) ◽  
pp. 131-138
Author(s):  
Turki Abdalla ◽  
Haroution Hairik ◽  
Adel Dakhil

This paper presents a method for improving the speed profile of a three phase induction motor in direct torque control (DTC) drive system using a proposed fuzzy logic based speed controller. A complete simulation of the conventional DTC and closed-loop for speed control of three phase induction motor was tested using well known Matlab/Simulink software package. The speed control of the induction motor is done by using the conventional proportional integral (PI) controller and the proposed fuzzy logic based controller. The proposed fuzzy logic controller has a nature of (PI) to determine the torque reference for the motor. The dynamic response has been clearly tested for both conventional and the proposed fuzzy logic based speed controllers. The simulation results showed a better dynamic performance of the induction motor when using the proposed fuzzy logic based speed controller compared with the conventional type with a fixed (PI) controller.


Direct Torque Control (DTC) of induction motor is preferred control strategy recently, due to its quick torque response, simplicity, less sensitivity against motor parameter variation. In general, PI speed controllers are widely used in industrial applications due to their simple structure. Due to the continuous variation of machine parameters, model uncertainties, nonlinear dynamics and system external disturbance, fixed gain PI controllers may becomes unable to provide the required control performance. Genetic Algorithm (GA) is used to tune the PI controller gains to ensure optimal performance. GA is more attractive for applications that involve non smooth or noisy signals. GA is used to minimize speed error and attains optimal values of the PI controller gains. The efficient and effective speed controllers can be designed by using adaptive control techniques. In which the conventional PI controller is replaced by structures based on Sliding Mode Control (SMC) strategy. SMC is known for its capability to cope with bounded disturbance as well as model imprecision which makes it ideal for the robust nonlinear control of IM drives


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