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首页> 外文期刊>Intelligent automation and soft computing >IMPROVED PARTICLE SWARM OPTIMIZATION BY UPDATING CONSTRAINTS OF PID CONTROL FOR REAL TIME LINEAR MOTOR POSITIONING
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IMPROVED PARTICLE SWARM OPTIMIZATION BY UPDATING CONSTRAINTS OF PID CONTROL FOR REAL TIME LINEAR MOTOR POSITIONING

机译:通过更新PID约束对实时线性电机定位进行改进的粒子群优化

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摘要

This paper proposes an Improved Particle Swarm Optimization (IPSO) technique for adjusting the gains of a Proportional-Integral-Derivative PID controller. The new approach introduces particle space constraints to improve velocity updating performance and position updating capability. This study presents numerical simulations and experimental results based on PID, PSO-PID, and IPSO-PID control systems. Real time experimental results show that the proposed IPSO algorithm has great computational convergence and ensures the stability of the controlled system without strict constraints on updating velocity. Tests on a linear synchronous motor (LSM) using a digital signal Microchip (dsPIC) processor demonstrate the effectiveness and robustness in positioning with disturbance excitation.
机译:本文提出了一种改进的粒子群优化(IPSO)技术,用于调节比例积分微分PID控制器的增益。新方法引入了粒子空间约束,以提高速度更新性能和位置更新能力。这项研究提供了基于PID,PSO-PID和IPSO-PID控制系统的数值模拟和实验结果。实时实验结果表明,所提出的IPSO算法具有很好的计算收敛性,并且在不受更新速度严格限制的情况下,可以确保受控系统的稳定性。使用数字信号Microchip(dsPIC)处理器在线性同步电动机(LSM)上进行的测试证明了在干扰激励下定位的有效性和鲁棒性。

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