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Energy efficient control of an induction machine using a chaos particle swarm optimization algorithm

机译:使用混沌粒子群优化算法能量控制感应机的控制

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This paper proposes a new application of a chaos particle swarm optimization (PSO) algorithm for loss model-based energy efficient control of an induction machine (IM) using an optimal rotor flux reference. The chaos PSO algorithm with a logistic map has been used for initializing a random value of the rotor flux reference, the inertia weight and two independent random sequences in the velocity update equation of the PSO algorithm. These result in the best convergence capability and search performance for the PSO algorithm in searching for an optimal rotor flux reference for energy efficient control of the IM. Additionally, this paper also proposes a recursive least-squares (RLS) algorithm with multiple time-varying forgetting factors for on-line parameter estimation of the IM. The estimated parameters are used to update IM parameter variations during operation. This means that the energy efficient control scheme is robust to parameter variations. Simulation results confirm the effectiveness of the proposed energy efficient control strategy.
机译:本文提出了使用最佳转子通量参考的混沌粒子群优化(PSO)算法的丢失模型的节能控制的新应用。具有逻辑图的混沌PSO算法已经用于初始化转子通量参考的随机值,惯性重量和PSO算法速度更新方程中的两个独立随机序列。这些导致PSO算法的最佳收敛能力和搜索性能,用于搜索最佳转子通量参考,以便IM的节能控制。另外,本文还提出了具有多个时变的遗忘因子的递归最小二乘法(RLS)算法,用于IM的在线参数估计。估计的参数用于在操作期间更新IM参数变型。这意味着节能控制方案对参数变化具有鲁棒性。仿真结果证实了所提出的节能控制策略的有效性。

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