In order to improve weapon assignment(WA)accuracy in real scenario,an artificial neural network(ANN)model is built to calculate real-time weapon kill probabilities.Considering the WA characteristic,each input represen...In order to improve weapon assignment(WA)accuracy in real scenario,an artificial neural network(ANN)model is built to calculate real-time weapon kill probabilities.Considering the WA characteristic,each input representing one assessment index should be normalized properly.Therefore,the modified WA model is oriented from constant value to dynamic computation.Then an improved invasive weed optimization algorithm is applied to solve the WA problem.During search process,local search is used to improve the initial population,and seed reproduction is redefined to guarantee the mutation from multipoint to single point.In addition,the idea of vaccination and immune selection in biology is added into optimization process.Finally,simulation results verify the model′s rationality and effectiveness of the proposed algorithm.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
基金Supported by the National Natural Science Foundation of China(11102080,61374212)the Science and Technology on Electro-Optic Control Laboratory and Aeronautical Science Foundation of China(20135152047)
文摘In order to improve weapon assignment(WA)accuracy in real scenario,an artificial neural network(ANN)model is built to calculate real-time weapon kill probabilities.Considering the WA characteristic,each input representing one assessment index should be normalized properly.Therefore,the modified WA model is oriented from constant value to dynamic computation.Then an improved invasive weed optimization algorithm is applied to solve the WA problem.During search process,local search is used to improve the initial population,and seed reproduction is redefined to guarantee the mutation from multipoint to single point.In addition,the idea of vaccination and immune selection in biology is added into optimization process.Finally,simulation results verify the model′s rationality and effectiveness of the proposed algorithm.
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。
