To track the nonlinear,non-Gaussian bearings-only maneuvering target accurately online,the constrained auxiliary particle filtering(CAPF)algorithm is presented.To restrict the samples into the feasible area,the soft m...To track the nonlinear,non-Gaussian bearings-only maneuvering target accurately online,the constrained auxiliary particle filtering(CAPF)algorithm is presented.To restrict the samples into the feasible area,the soft measurement constraints are implemented into the update routine via the1 regularization.Meanwhile,to enhance the sampling diversity and efficiency,the target kinetic features and the latest observations are involved into the evolution.To take advantage of the past and the current measurement information simultaneously,the sub-optimal importance distribution is constructed as a Gaussian mixture consisting of the original and modified priors with the fuzzy weighted factors.As a result,the corresponding weights are more evenly distributed,and the posterior distribution of interest is approximated well with a heavier tailor.Simulation results demonstrate the validity and superiority of the CAPF algorithm in terms of efficiency and robustness.展开更多
The choice of the particle's distribution model and the consistency of the result are very important for FastSLAM.The improved auxiliary variable model with FastSLAM,and Stirling Interpolation which is used to app...The choice of the particle's distribution model and the consistency of the result are very important for FastSLAM.The improved auxiliary variable model with FastSLAM,and Stirling Interpolation which is used to approximate the nonlinear functions are provided.This approach improves the precision of the approximation for the nonlinear functions,conquers the drawback of the FastSLAM1.0 by using a model ignoring the measurement data,enhances the estimation consistency of the robot pose,and reduces the degradation speed of the particle in FastSLAM algorithm.Simulation results demonstrate the excellence of the proposed algorithm and give the noise parameter influence on the proposed algorithm.展开更多
针对有源电力滤波器APF(Active Power Filter)中,电流补偿PI控制器参数难以整定的问题,提出了一种基于FPGA实现的粒子群优化PI控制器设计方案。利用粒子群优化算法对非线形系统的适应性强和易于工程实现等特点,同时以FPGA为硬件核心处理...针对有源电力滤波器APF(Active Power Filter)中,电流补偿PI控制器参数难以整定的问题,提出了一种基于FPGA实现的粒子群优化PI控制器设计方案。利用粒子群优化算法对非线形系统的适应性强和易于工程实现等特点,同时以FPGA为硬件核心处理器,对电流补偿PI控制器的比例、积分参数进行优化。仿真和样机实验结果表明,优化后的PI控制器在动态性能以及控制精度等方面有明显提高,基于该PI控制器的有源电力滤波器能迅速有效产生补偿电流,抑制电网谐波,证明了该设计的可行性。展开更多
基金supported by the National Natural Science Foundation of China(61773267)the Shenzhen Fundamental Research Project(JCYJ2017030214551952420170818102503604)
文摘To track the nonlinear,non-Gaussian bearings-only maneuvering target accurately online,the constrained auxiliary particle filtering(CAPF)algorithm is presented.To restrict the samples into the feasible area,the soft measurement constraints are implemented into the update routine via the1 regularization.Meanwhile,to enhance the sampling diversity and efficiency,the target kinetic features and the latest observations are involved into the evolution.To take advantage of the past and the current measurement information simultaneously,the sub-optimal importance distribution is constructed as a Gaussian mixture consisting of the original and modified priors with the fuzzy weighted factors.As a result,the corresponding weights are more evenly distributed,and the posterior distribution of interest is approximated well with a heavier tailor.Simulation results demonstrate the validity and superiority of the CAPF algorithm in terms of efficiency and robustness.
基金National High-Tech Research and Development Program of China(No.2003AA1Z2130)Science and Technology Project of Zhejiang Province,China(No.2005C11001-02)
文摘The choice of the particle's distribution model and the consistency of the result are very important for FastSLAM.The improved auxiliary variable model with FastSLAM,and Stirling Interpolation which is used to approximate the nonlinear functions are provided.This approach improves the precision of the approximation for the nonlinear functions,conquers the drawback of the FastSLAM1.0 by using a model ignoring the measurement data,enhances the estimation consistency of the robot pose,and reduces the degradation speed of the particle in FastSLAM algorithm.Simulation results demonstrate the excellence of the proposed algorithm and give the noise parameter influence on the proposed algorithm.
文摘针对有源电力滤波器APF(Active Power Filter)中,电流补偿PI控制器参数难以整定的问题,提出了一种基于FPGA实现的粒子群优化PI控制器设计方案。利用粒子群优化算法对非线形系统的适应性强和易于工程实现等特点,同时以FPGA为硬件核心处理器,对电流补偿PI控制器的比例、积分参数进行优化。仿真和样机实验结果表明,优化后的PI控制器在动态性能以及控制精度等方面有明显提高,基于该PI控制器的有源电力滤波器能迅速有效产生补偿电流,抑制电网谐波,证明了该设计的可行性。
