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Application of Independent-minded Particle Swarm Optimization for design of class-E amplifiers

机译:独立思想粒子群算法在E类放大器设计中的应用

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摘要

The class-E amplifier is one of the switching amplifiers, which satisfies the class-E switching conditions. It is, however, difficult to determine the values of the passive elements included in the circuit for achieving the class-E switching conditions. Recently, the Newton type algorithm is proposed to determine the passive elements. However, this method requires a good initial estimation. In this paper, an algorithm using Independent-minded Particle Swarm Optimization (IPSO) is introduced to estimate the initial conditions. To find it efficiently, the MOSFET in the class-E amplifier is replaced with an ideal switch and the objective function for the optimization is efficiently evaluated. Unfortunately, the objective function has multimodal characteristics and a robust optimization method is required. Then, the optimum solution is found by using IPSO which shows good performances for multimodal cases. Therefore, the initial estimation for the Newton type algorithm is easily obtained and a good design of the class-E amplifier becomes available.
机译:E类放大器是满足E类开关条件的开关放大器之一。然而,难以确定用于实现E类开关条件的电路中包括的无源元件的值。最近,提出了牛顿型算法来确定无源元件。但是,此方法需要良好的初始估计。本文介绍了一种使用独立思想粒子群优化算法(IPSO)估计初始条件的算法。为了有效地找到它,用理想的开关代替了E类放大器中的MOSFET,并有效地评估了优化的目标函数。不幸的是,目标函数具有多峰特性,因此需要鲁棒的优化方法。然后,通过使用IPSO找到最佳解决方案,该解决方案在多模式情况下表现出良好的性能。因此,容易获得牛顿型算法的初始估计,并且可以得到良好的E类放大器设计。

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