Search - speed particle swarm optimization

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[Industry research] 1 DL : 0: During the last decade, many variants of the original particle swarm optimization (PSO) algorithm have been proposed. In many cases, the difference between two variants can be seen as an algorithmic component being present in one variant but not in the other. In the first part of the paper, we present the results and insights obtained from a detailed empirical study of several PSO variants from a component difference point of view. In the second part of the paper, we propose a new PSO algorithm that combines a number of algorithmic components that showed distinct advantages in the experimental study concerning optimization speed and reliability. We call this composite algorithm Frankenstein’s PSO in an analogy to the popular character of Mary Shelley’s novel. Frankenstein’s PSO performance evaluation shows that by integrating components in novel ways effective optimizers can be designed.
Date : 2026-01-07 Size : 294kb User : omid
[Industry research] estimation-extended-Kalman-filter DL : 0: 针对感应电机扩展卡尔曼滤波器转速估计中难以取得卡尔曼滤波器系统噪声矩阵和测量噪声矩阵最优值的问题，提出了一种基于改进粒子群算法优化的扩展卡尔曼滤波器转速估计方法。算法通过融合遗传算法和粒子群算法的优点，采用可调整的算法模型对粒子群算法进行改进，将改进的粒子群算法对扩展卡尔曼滤波器中的系统噪声矩阵和测量噪声矩阵进行优化处理，将优化后的卡尔曼滤波器应用于感应电机转速估计。- Extended Kalman Filter for induction motor speed estimation problem is difficult to obtain a Kalman filter system noise matrix and the measurement noise matrix optimal value proposed speed estimation method based on improved particle swarm optimization of the extended Kalman filter. By virtue of the genetic algorithm and particle swarm optimization algorithm fusion algorithm using the adjustable model PSO improvements that will improve the PSO extended Kalman filter system noise matrix and the measurement noise matrix optimization process, the optimized Kalman filter is applied to the induction motor speed estimate.
Date : 2026-01-07 Size : 1.15mb User : 周
[Industry research] Particle Swarm Optimization of an Extended Kalman Filter for speed and rotor flux estimation of an induction motor drive DL : 0: A novel method based on a combination of the Extended Kalman Filter (EKF) with Particle Swarm Optimization (PSO) to estimate the speed and rotor flux of an induction motor driveis presented. The proposed method will be performed in two steps. As a first step, the covariance matrices of state noise and measurement noise will be optimized in an off-line manner by the PSO algorithm. As a second step, the optimal values of the above covariance matrices are injected in our speed-rotor flux estimation loop (on-line).Computer simulations of the speed and rotor-flux estimation have been performed in order to investigate the effectiveness of the proposed method. Simulations and comparison with genetic algorithms (GAs) show that the results are very encouraging and achieve good performances.
Date : 2019-01-08 Size : 650.15kb User : pudn0507@yahoo.fr