A polynomial model, time origin shifting model(TOSM, is used to describe the trajectory of a moving target .Based on TOSM, a recursive laeast squares(RLS) algorithm with varied forgetting factor is derived for tracki...A polynomial model, time origin shifting model(TOSM, is used to describe the trajectory of a moving target .Based on TOSM, a recursive laeast squares(RLS) algorithm with varied forgetting factor is derived for tracking of a non-maneuvering target. In order to apply this algorithm to maneuvering targets tracking ,a tracking signal is performed on-line to determine what kind of TOSm will be in effect to track a target with different dynamics. An effective multiple model least squares filtering and forecasting method dadpted to real tracking of a maneuvering target is formulated. The algorithm is computationally more effcient than Kalman filter and the percentage improvement from simulations show both of them are considerably alike to some extent.展开更多
The combination of structural health monitoring and vibration control is of great importance to provide components of smart structures.While synthetic algorithms have been proposed,adaptive control that is compatible ...The combination of structural health monitoring and vibration control is of great importance to provide components of smart structures.While synthetic algorithms have been proposed,adaptive control that is compatible with changing conditions still needs to be used,and time-varying systems are required to be simultaneously estimated with the application of adaptive control.In this research,the identification of structural time-varying dynamic characteristics and optimized simple adaptive control are integrated.First,reduced variations of physical parameters are estimated online using the multiple forgetting factor recursive least squares(MFRLS)method.Then,the energy from the structural vibration is simultaneously specified to optimize the control force with the identified parameters to be operational.Optimization is also performed based on the probability density function of the energy under the seismic excitation at any time.Finally,the optimal control force is obtained by the simple adaptive control(SAC)algorithm and energy coefficient.A numerical example and benchmark structure are employed to investigate the efficiency of the proposed approach.The simulation results revealed the effectiveness of the integrated online identification and optimal adaptive control in systems.展开更多
为了实现永磁同步直线电机PMSLM(permanent magnet synchronous linear motor)高精度的多电气参数在线辨识,提出了一种基于双模型的递推最小二乘电气参数在线辨识算法。首先,根据电机的dq轴电压方程分别建立了辨识定子电阻、永磁体磁链...为了实现永磁同步直线电机PMSLM(permanent magnet synchronous linear motor)高精度的多电气参数在线辨识,提出了一种基于双模型的递推最小二乘电气参数在线辨识算法。首先,根据电机的dq轴电压方程分别建立了辨识定子电阻、永磁体磁链的模型1和辨识q轴电感、d轴电感的模型2,并将2个辨识模型循环结合。其次,基于上述双模型结构,采用递推最小二乘算法实现电气参数在线辨识,并针对PMSLM运行时存在大量动态过程的特性,提出一种具有饱和特性的分段变遗忘因子;然后,对功率开关非理想因素导致的误差电压进行补偿,进一步提高了辨识的精准度;最后,仿真和实验结果证明了该辨识算法的有效性,且具有收敛速度快、辨识结果精度高、多工况适用等优点。展开更多
高能动力电池是供配电系统的核心储能模块,针对高能动力电池的应用构建了二阶等效电路模型。在等效电路模型的基础上,提出联合递推最小二乘(Recursive Least Squares,RLS)法和扩展卡尔曼滤波(Extended Kalman Filter,EKF)的荷电状态(Sta...高能动力电池是供配电系统的核心储能模块,针对高能动力电池的应用构建了二阶等效电路模型。在等效电路模型的基础上,提出联合递推最小二乘(Recursive Least Squares,RLS)法和扩展卡尔曼滤波(Extended Kalman Filter,EKF)的荷电状态(Stage of Charge,SOC)算法,并在其基础上改进为基于温度补偿的联合RLS法和EKF融合的SOC算法。基于MATLAB软件,设计改进前和改进后联合算法的仿真验证程序,并对结果进行了比较分析。仿真结果表明,基于温度补偿的联合算法可实现当SOC处于(0.25,1)的区域内,相对误差基本小于5%,验证了所提出的建模方法和求解方法的有效性。展开更多
文摘A polynomial model, time origin shifting model(TOSM, is used to describe the trajectory of a moving target .Based on TOSM, a recursive laeast squares(RLS) algorithm with varied forgetting factor is derived for tracking of a non-maneuvering target. In order to apply this algorithm to maneuvering targets tracking ,a tracking signal is performed on-line to determine what kind of TOSm will be in effect to track a target with different dynamics. An effective multiple model least squares filtering and forecasting method dadpted to real tracking of a maneuvering target is formulated. The algorithm is computationally more effcient than Kalman filter and the percentage improvement from simulations show both of them are considerably alike to some extent.
文摘The combination of structural health monitoring and vibration control is of great importance to provide components of smart structures.While synthetic algorithms have been proposed,adaptive control that is compatible with changing conditions still needs to be used,and time-varying systems are required to be simultaneously estimated with the application of adaptive control.In this research,the identification of structural time-varying dynamic characteristics and optimized simple adaptive control are integrated.First,reduced variations of physical parameters are estimated online using the multiple forgetting factor recursive least squares(MFRLS)method.Then,the energy from the structural vibration is simultaneously specified to optimize the control force with the identified parameters to be operational.Optimization is also performed based on the probability density function of the energy under the seismic excitation at any time.Finally,the optimal control force is obtained by the simple adaptive control(SAC)algorithm and energy coefficient.A numerical example and benchmark structure are employed to investigate the efficiency of the proposed approach.The simulation results revealed the effectiveness of the integrated online identification and optimal adaptive control in systems.
文摘为了实现永磁同步直线电机PMSLM(permanent magnet synchronous linear motor)高精度的多电气参数在线辨识,提出了一种基于双模型的递推最小二乘电气参数在线辨识算法。首先,根据电机的dq轴电压方程分别建立了辨识定子电阻、永磁体磁链的模型1和辨识q轴电感、d轴电感的模型2,并将2个辨识模型循环结合。其次,基于上述双模型结构,采用递推最小二乘算法实现电气参数在线辨识,并针对PMSLM运行时存在大量动态过程的特性,提出一种具有饱和特性的分段变遗忘因子;然后,对功率开关非理想因素导致的误差电压进行补偿,进一步提高了辨识的精准度;最后,仿真和实验结果证明了该辨识算法的有效性,且具有收敛速度快、辨识结果精度高、多工况适用等优点。
文摘高能动力电池是供配电系统的核心储能模块,针对高能动力电池的应用构建了二阶等效电路模型。在等效电路模型的基础上,提出联合递推最小二乘(Recursive Least Squares,RLS)法和扩展卡尔曼滤波(Extended Kalman Filter,EKF)的荷电状态(Stage of Charge,SOC)算法,并在其基础上改进为基于温度补偿的联合RLS法和EKF融合的SOC算法。基于MATLAB软件,设计改进前和改进后联合算法的仿真验证程序,并对结果进行了比较分析。仿真结果表明,基于温度补偿的联合算法可实现当SOC处于(0.25,1)的区域内,相对误差基本小于5%,验证了所提出的建模方法和求解方法的有效性。
