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Analyses and Control of Chaotic Behavior in DC-DC Converters

机译:DC-DC转换器中混沌行为的分析与控制

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In this study the nonlinear behavior of a buck converter was simulated and the responses of Phases 1 and 2 and the chaotic phase were investigated using changes of input voltage. After a dynamic system model had been acquired using basic electronic circuit theory, Matlab and Pspice simulations were used to study system inductance, resistance, and capacitance. The characteristic changes of input voltage, and phase plane traces from simulation and experiments showed nonlinear behavior in Phases 1 and 2, as well as a chaotic phase. PID control and Integral Absolute Error (IAE) were used as adaption coefficients to control chaotic behavior, and particle swarm optimization (PSO) and the genetic algorithm were used to find the optimal gain parameters for the PID controller. Simulation results showed that the control of chaotic phenomena could be achieved and errors were close to zero. Fuzzy control was also used effectively to prevent chaos. The experimental results also showed nonlinear behavior from Phases 1 and 2 as well as the chaotic phase. Laboratory experiments conducted using both PID and fuzzy control echoed the simulation results. The fuzzy control results were somewhat better than those obtained with PID.
机译:在本研究中,模拟了降压转换器的非线性行为,并利用输入电压的变化研究了相位1和2以及混沌相位的响应。在使用基本的电子电路理论获得了动态系统模型之后,使用Matlab和Pspice仿真研究了系统电感,电阻和电容。输入电压的特性变化以及来自仿真和实验的相平面迹线显示出阶段1和阶段2以及混沌阶段的非线性行为。 PID控制和积分绝对误差(IAE)被用作控制混沌行为的自适应系数,粒子群优化(PSO)和遗传算法被用来找到PID控制器的最佳增益参数。仿真结果表明,可以实现对混沌现象的控制,误差接近于零。模糊控制也被有效地用来防止混乱。实验结果还显示出阶段1和阶段2以及混沌阶段的非线性行为。使用PID和模糊控制进行的实验室实验与模拟结果相呼应。模糊控制的结果要好于PID的结果。

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