RESUMO
Heteroatom-doped 3D porous carbon materials have been synthesized by utilizing hydroxyapatite in pig bones as a self-template and used as electrode materials for symmetric supercapacitors, which exhibit ultra-high energy density both in an aqueous electrolyte and organic electrolyte, showing great potential applications in the next generation of energy storage and conversion devices.
RESUMO
In most practical applications, the tracking process needs to update the data constantly. However, outliers may occur frequently in the process of sensors' data collection and sending, which affects the performance of the system state estimate. In order to suppress the impact of observation outliers in the process of target tracking, a novel filtering algorithm, namely a robust adaptive unscented Kalman filter, is proposed. The cost function of the proposed filtering algorithm is derived based on fading factor and maximum correntropy criterion. In this paper, the derivations of cost function and fading factor are given in detail, which enables the proposed algorithm to be robust. Finally, the simulation results show that the presented algorithm has good performance, and it improves the robustness of a general unscented Kalman filter and solves the problem of outliers in system.