Tuning of PID Controller Coefficients for AVR Systems by Simulated Annealing Algorithm

As a real time process, in tuning the coefficients of PID controllers in AVRs, accuracy vs. speed is an important issue. Considering complexity of the problem and real systems requirements, various methods, including exact methods and approximation algorithms, have been implemented for this purpose....

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Bibliographic Details
Published in:Majlesi journal of electrical engineering Vol. 15; no. 1; pp. 25 - 31
Main Authors: Ehsani, Maryam, Shafiezad, Morassae
Format: Journal Article
Language:English
Published: Isfahan Islamic Azad University Majlesi 01.03.2021
Subjects:
Algorithms
Approximation
Coefficients
Complexity
Equilibrium
Fuzzy logic
Genetic algorithms
Heuristic methods
Methods
Multiple objective analysis
Optimization algorithms
Proportional integral derivative
Simulated annealing
Software
Time response
Tuning
ISSN:2008-1413, 2008-1413
Online Access:Get full text
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Summary:As a real time process, in tuning the coefficients of PID controllers in AVRs, accuracy vs. speed is an important issue. Considering complexity of the problem and real systems requirements, various methods, including exact methods and approximation algorithms, have been implemented for this purpose. Since the conventional methods based on metaheuristic algorithms solving this problem, generally use population-based algorithms such as GA and PSO, this paper aims to investigate the efficiency and performance of single- solution based metaheuristics to solve this problem. So Simulated Annealing (SA) algorithm is proposed, and implemented for optimizing PID coefficients. In addition, an extension of SA is presented improving the search strategy based on neighborhood adjustment. The results indicate that the proposed algorithms as single based metaheuristics, have a good or even better performance vs. population based metaheuristics, in spite of simplicity in implementation and less computation requirements. This fact implies that the landscape complexity of these problems does not necessarily require population-based algorithms. The presented method is also applied to multiple objective functions regarding different time response criteria in output voltage and leads to better results in less time.
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ISSN:2008-1413
2008-1413
DOI:10.29252/mjee.15.1.25