Particle swarm optimization(PSO) and invasive weed optimization(IWO) algorithms are used for extracting the modeling parameters of materials useful for optics and photonics research community. These two bio-inspired a...Particle swarm optimization(PSO) and invasive weed optimization(IWO) algorithms are used for extracting the modeling parameters of materials useful for optics and photonics research community. These two bio-inspired algorithms are used here for the first time in this particular field to the best of our knowledge. The algorithms are used for modeling graphene oxide and the performances of the two are compared. Two objective functions are used for different boundary values. Root mean square(RMS) deviation is determined and compared.展开更多
针对永磁同步直线电机没有中间传动环节,任何不确定性扰动都会直接影响控制系统性能的问题,设计了一种改进杂草算法优化的PMLSM(Permanent Magnet Linear Synchronous Motor)二阶自抗扰控制器。通过采用混沌反向学习初始化方法和柯西分...针对永磁同步直线电机没有中间传动环节,任何不确定性扰动都会直接影响控制系统性能的问题,设计了一种改进杂草算法优化的PMLSM(Permanent Magnet Linear Synchronous Motor)二阶自抗扰控制器。通过采用混沌反向学习初始化方法和柯西分布的空间分布方式改进杂草算法优化自抗扰控制器参数,经过优化的自抗扰控制器的控制其性能有明显提高。仿真结果表明,该自抗扰控制器响应速度快,稳态误差减小2%且无超调,对负载扰动具有良好的鲁棒性。展开更多
文摘Particle swarm optimization(PSO) and invasive weed optimization(IWO) algorithms are used for extracting the modeling parameters of materials useful for optics and photonics research community. These two bio-inspired algorithms are used here for the first time in this particular field to the best of our knowledge. The algorithms are used for modeling graphene oxide and the performances of the two are compared. Two objective functions are used for different boundary values. Root mean square(RMS) deviation is determined and compared.
文摘针对永磁同步直线电机没有中间传动环节,任何不确定性扰动都会直接影响控制系统性能的问题,设计了一种改进杂草算法优化的PMLSM(Permanent Magnet Linear Synchronous Motor)二阶自抗扰控制器。通过采用混沌反向学习初始化方法和柯西分布的空间分布方式改进杂草算法优化自抗扰控制器参数,经过优化的自抗扰控制器的控制其性能有明显提高。仿真结果表明,该自抗扰控制器响应速度快,稳态误差减小2%且无超调,对负载扰动具有良好的鲁棒性。
