节点定位是无线传感器网络中最为关键的一项技术。针对无源定位的问题,提出一种到达时间差(TDOA)和到达信号增益比(GROA)联合定位算法,并且采用飞行机制的萤火虫算法(GSO)来求得最终结果。结合TDOA和GROA定位模型,引入辅助变量将方程伪...节点定位是无线传感器网络中最为关键的一项技术。针对无源定位的问题,提出一种到达时间差(TDOA)和到达信号增益比(GROA)联合定位算法,并且采用飞行机制的萤火虫算法(GSO)来求得最终结果。结合TDOA和GROA定位模型,引入辅助变量将方程伪线性化;然后采用修正两步加权最小二乘算法(TSWLS)来进行求解。并且在不影响收敛速度和精度的前提下,采用带有飞行机制的GSO算法来寻求目标定位的最优解,克服粒子群算法易陷入局部最优的缺点。仿真结果表明,该算法相比较TDOA算法,定位精度提高了23 d B,并且具有相对较高和较稳定的定位精度。展开更多
针对基于Levenberg-Marquardt方法辨识黄酒发酵过程模型参数时易陷入局部最优,收敛速度慢,很难准确获取具有强泛化能力的模型参数的问题,提出了一种具有莱维飞行机制和柯西变异的蚁狮优化算法(ant lion optimization with Levy flight a...针对基于Levenberg-Marquardt方法辨识黄酒发酵过程模型参数时易陷入局部最优,收敛速度慢,很难准确获取具有强泛化能力的模型参数的问题,提出了一种具有莱维飞行机制和柯西变异的蚁狮优化算法(ant lion optimization with Levy flight and Cauchy mutation,LCALO),该算法采用基于莱维飞行和柯西变异来解决这类问题。莱维飞行可以提高算法的全局搜索能力,而柯西变异有助于避免陷入局部最优。结果表明,相比于遗传算法、粒子群算法和蚁狮算法,LCALO的收敛速度快,具有全局搜索能力和局部开发能力好的优点。最后将改进算法应用于黄酒发酵模型的参数辨识,仿真结果证明该算法具有较好的参数辨识能力。展开更多
In this paper,an active fault-tolerant control(FTC)strategy of aerial manipulators based on non-singular terminal sliding mode(NTSM)and extended state observer(ESO)is proposed.Firstly,back-stepping technology is adopt...In this paper,an active fault-tolerant control(FTC)strategy of aerial manipulators based on non-singular terminal sliding mode(NTSM)and extended state observer(ESO)is proposed.Firstly,back-stepping technology is adopted as the control framework to ensure the global asymptotic stability of the closed-loop system.Next,the NTSM with estimated parameters of actuator faults is used as main robustness controller to deal with actuator faults.Then,the ESO is utilized to estimate and compensate the complex coupling effects and external disturbances.The Lyapunov stability theory can guarantee the asymptotic stability of aerial manipulators system with actuator faults and external disturbances.The proposed FTC scheme considers both actuator fault and modelling errors,combined with the adaptive law of actuator fault,which has better performance than traditional FTC scheme,such as NTSM.Finally,several comparative simulations are conducted to illustrate the effectiveness of the proposed FTC scheme.展开更多
文摘节点定位是无线传感器网络中最为关键的一项技术。针对无源定位的问题,提出一种到达时间差(TDOA)和到达信号增益比(GROA)联合定位算法,并且采用飞行机制的萤火虫算法(GSO)来求得最终结果。结合TDOA和GROA定位模型,引入辅助变量将方程伪线性化;然后采用修正两步加权最小二乘算法(TSWLS)来进行求解。并且在不影响收敛速度和精度的前提下,采用带有飞行机制的GSO算法来寻求目标定位的最优解,克服粒子群算法易陷入局部最优的缺点。仿真结果表明,该算法相比较TDOA算法,定位精度提高了23 d B,并且具有相对较高和较稳定的定位精度。
文摘针对基于Levenberg-Marquardt方法辨识黄酒发酵过程模型参数时易陷入局部最优,收敛速度慢,很难准确获取具有强泛化能力的模型参数的问题,提出了一种具有莱维飞行机制和柯西变异的蚁狮优化算法(ant lion optimization with Levy flight and Cauchy mutation,LCALO),该算法采用基于莱维飞行和柯西变异来解决这类问题。莱维飞行可以提高算法的全局搜索能力,而柯西变异有助于避免陷入局部最优。结果表明,相比于遗传算法、粒子群算法和蚁狮算法,LCALO的收敛速度快,具有全局搜索能力和局部开发能力好的优点。最后将改进算法应用于黄酒发酵模型的参数辨识,仿真结果证明该算法具有较好的参数辨识能力。
基金Project(51705243)supported by National Natural Science Foundation of ChinaProject(NS2020052)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(GZKF-201915)supported by the Open Foundation of the State Key Laboratory of Fluid Power and Mechatronic Systems,China。
文摘In this paper,an active fault-tolerant control(FTC)strategy of aerial manipulators based on non-singular terminal sliding mode(NTSM)and extended state observer(ESO)is proposed.Firstly,back-stepping technology is adopted as the control framework to ensure the global asymptotic stability of the closed-loop system.Next,the NTSM with estimated parameters of actuator faults is used as main robustness controller to deal with actuator faults.Then,the ESO is utilized to estimate and compensate the complex coupling effects and external disturbances.The Lyapunov stability theory can guarantee the asymptotic stability of aerial manipulators system with actuator faults and external disturbances.The proposed FTC scheme considers both actuator fault and modelling errors,combined with the adaptive law of actuator fault,which has better performance than traditional FTC scheme,such as NTSM.Finally,several comparative simulations are conducted to illustrate the effectiveness of the proposed FTC scheme.
