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An Optimal PID Controller for a Bidirectional Inductive Power Transfer System Using Multiobjective Genetic Algorithm

delete2014-03-01
delete211
PRE
AI
A
Akshya Swain
U
Udaya K. Madawala
D
Duleepa J. Thrimawithana
DOI:10.1109/TPEL.2013.2262953delete
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摘要

摘要

En 中文
Bidirectional inductive power transfer (IPT) systems are suitable for applications that require wireless and two-way power transfer. However, these systems are high-order resonant networks in nature and, hence, design and implementation of an optimum proportional-integral-derivative (PID) controller using various conventional methods is an onerous exercise. Further, the design of a PID controller, meeting various and demanding specifications, is a multiobjective problem and direct optimization of the PID gains often lead to a nonconvex problem. To overcome the difficulties associated with the traditional PID tuning methods, this paper, therefore, proposes a derivative-free optimization technique, based on genetic algorithm (GA), to determine the optimal parameters of PID controllers used in bidirectional IPT systems. The GA determines the optimal gains at a reasonable computational cost and often does not get trapped in a local optimum. The performance of the GA-tuned controller is investigated using several objective functions and under various operating conditions in comparison to other traditional tuning methods. It was observed that the performance of the GA-based PID controller is dependent on the nature of the objective function and therefore an objective function, which is a weighted combination of rise time, settling time, and peak overshoot, is used in determining the parameters of the PID controller using multiobjective GA. Simulated and experimental results of a 1-kW prototype bidirectional IPT system are presented to demonstrate the effectiveness of the GA-tuned controller as well as to show that gain selection through multiobjective GA using the weighted objective function yields the best performance of the PID controller.
Keyword:
Contactless power transfer
electric vehicles (EVs)
inductive power transmission
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期刊

IEEE Transactions on Power Electronics 封面图
IEEE Transactions on Power Electronics
IF:
6.5
论文数:
1.7W
被引数:
8.3W

机构

U
University of Auckland
学者数:
2.3W
论文数: 2.4W
被引数: 3.3W
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