(2015) Parameter identification of BIPT system using chaotic-enhanced fruit fly optimization algorithm. Applied Mathematics and Computation, 268 . pp. 1267-1281 Bidirectional inductive power transfer (BIPT) system facilitates contactless power transfer between two sides and across an air-gap, through weak magnetic coupling. Typically, this system is nonlinear high order system which includes nonlinear switch components and resonant networks, developing of accurate model is a challenging task. In this paper, a novel technique for parameter identification of a BIPT system is presented by using chaotic-enhanced fruit fly optimization algorithm (CFOA). The fruit fly optimization algorithm (FOA) is a new metaheuristic technique based on the swarm behavior of the fruit fly. This paper proposes a novel CFOA, which employs chaotic sequence to enhance the global optimization capacity of original FOA. The parameter identification of the BIPT system is formalized as a multi-dimensional optimization problem, and an objective function is established minimizing the errors between the estimated and measured values. All the 11 parameters of this system (L pi , L T , L si , L so , C T , C s , M, R pi , R T , R si and R so ) can be identified simultaneously using measured input-output data. Simulations show that the proposed parameter identification technique is robust to measurements noise and variation of operation condition and thus it is suitable for practical application.
Bidirectional inductive power transfer (IPT) system facilitates contactless power transfer between two sides and across an air gap, through weak magnetic coupling. Typically, this system constitutes a high-order resonant circuit and, as such, is difficult to design and control. In this study, a novel technique for parameter identification of bidirectional IPT system is presented by using chaotic asexual reproduction optimization (CARO). The asexual reproduction optimization (ARO) is a novel kind of evolutionary-based algorithm that mathematically models the budding mechanism of asexual reproduction. The CARO employs chaotic sequence to enhance ARO's global searching ability. The parameter identification of a bidirectional IPT system is posed as an optimization process with an objective function minimizing the errors between the estimated and measured value. The implementation of the CARO-based parameter identification technique is analyzed in detail. Simulations are used to test the robustness and generalization ability of the proposed technique.
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