期刊
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
卷 47, 期 11, 页码 13729-13747出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s13369-021-06383-z
关键词
Levy flight distribution; Simulated annealing; Fractional-order PID controller; Hybrid algorithm
This study uses a FOPID controller and a hybridized metaheuristic algorithm to achieve optimum performance for a buck converter. The proposed algorithm shows significant improvement in the control performance of the closed-loop output voltage.
One of the main challenges in power converters is to adopt a convenient controller that is designed with an appropriate approach. In terms of controllers, linear and nonlinear types are available. Nonlinear controllers may be good for achieving dynamic capabilities; however, designing them involves undesirable complexity. Thus, alternative linear counterparts are desirable to achieve optimum performance. Fractional-order proportional-integral derivative (FOPID) controller stands as a good choice for this purpose since it is a more capable version of one of widely adopted linear controller known as PID. Therefore, in this study, a FOPID controller was used to achieve optimum performance for a buck converter. To obtain the best performance, a novel hybridized metaheuristic algorithm, which combines both Levy flight distribution and simulated annealing algorithms (LFDSA), was utilized. The developed algorithm involves a balanced structure in terms of explorative and exploitative phases, which was confirmed via performing related analysis on unimodal and multimodal benchmark functions. Non-parametric statistical test has also showed the better capability of the proposed algorithm. Due to its enhanced capability, the proposed algorithm helped achieving optimum values of FOPID parameters such that a better closed-loop output voltage control performance of the buck converter in terms of time and frequency domain responses as well as disturbance rejection have been achieved. The proposed LFDSA-based FOPID controller also tested against other capable and reported state-of-the-art algorithm and the results have also verified the superior capability of the LFDSA over other approaches.
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