A New Strategy-Based PID Controller Optimized by Genetic Algorithm for DTC of the Doubly Fed Induction Motor

Said Mahfoud,Mohammed El Mahfoud,Mohammed Taoussi,Najib El Ouanjli,Aziz Derouich

doi:10.3390/systems9020037

Said Mahfoud, Mohammed El Mahfoud + Show 3 more

Open Access

https://doi.org/10.3390/systems9020037

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Journal: Systems	Publication Date: May 24, 2021
Citations: 36	License type: CC BY 4.0

Affiliation: Sidi Mohamed Ben Abdellah University

Abstract

Proportional Integral Derivative (PID) is the most popular controller used in automatic systems, because of its robustness, ability to adapt the behaviors of the system, making them converge toward its optimum. These advantages are valid only in the case of the linear systems, as they present poor robustness in nonlinear systems. For that reason, many solutions are adopted to improve the PID robustness of the nonlinear systems. The optimization algorithm presents an efficient solution to generate the optimums PID gains adapting to the system’s nonlinearity. The regulation speed in the Direct Torque Control (DTC) is carried out by the PID controller, which caused many inconveniences in terms of speed (overshoot and rejection time), fluxes, and torque ripples. For that, this work describes a new approach for DTC of the Doubly Fed Induction Motor (DFIM) powered by two voltage inverters, using a PID controller for the regulation speed, based on a Genetic Algorithm (GA), which has been proposed for adjustment and optimizing the parameters of the PID controller, using a weighted combination of objective functions. To overcome the disadvantages cited at the beginning, the new hybrid approach GA-DTC has the efficiency to adapt to the system’s nonlinearity. This proposed strategy has been validated and implemented on Matlab/Simulink, which is attributed to many improvements in DFIM performances, such as limiting speed overshoot, reducing response time and the rate of Total Harmonic Distortion (THD) of the stator and rotor currents, and minimizing the rejection time of speed and amplitude of the torque and flux ripples.

Highlights

In the mid-1980s, the development of new signal processing techniques led to the realization of much more advanced control structures
The values of the Proportional Integral Derivative (PID) controller parameters generated by the Genetic Algorithm (GA) are within the variation bands shown in Table 2; the system is configured with the parameters in Tables A1 and A2 mentioned in the Appendix A, and the system is subjected to speed and torque references; the Tables A3 and A4 present the Nomenclature and Abbreviation of the various parameters of the system and the technical terms used in this article
We found the optimal simulation result cording to the criteria of choice of the GA parameters, which presents an essential ste all the optimization algorithms to have found the optimal results; the following fig Application of a nominal load of

Summary

Introduction

In the mid-1980s, the development of new signal processing techniques led to the realization of much more advanced control structures. The advantages attributed to the DTC technique (dynamics, robustness, less sensitivity to parametric variation, ease of implementation, high performance), are counterbalanced by the use of the hysteresis comparator; in principle, the comparator leads to variable frequency operation, and on the other hand, the finite frequency sampling results in a pseudo-random overshoot of the hysteresis band [4], operation at low speed and in particular, with variations in motor resistance, affects the behavior of the motor [5] These factors make it difficult to predict the harmonic content of the various output signals [6]. The application of the classic DTC to the DFIM induces torque oscillations that can stimulate mechanical resonances as they cause vibrations and audible noise, contributing to the early aging of the machine [7].

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Results

Conclusion