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A Simpler Algorithm of Generation Biconnected Rooted Outerplanar Graphs
Bingbing Zhuang 한국정보과학회 2011 한국정보과학회 학술발표논문집 Vol.38 No.1B
For given g ≥ 3, this paper provides an O(1) time and O(n) space complexity algorithm for generation of biconnected rooted colored outerplanar graphs with face size bound g, where the graphs generated contain at most n vertices. The vertices are colored in such a way that each color has a corresponding degree bound. There is also a face size bound for each inner face of the graph. No duplications or isomorphic copies of a same graph are generated.
Interacting Multiple Model Estimation-based Adaptive Robust Unscented Kalman Filter
Bingbing Gao,Shesheng Gao,Yongmin Zhong,Gaoge Hu,Chengfan Gu 제어·로봇·시스템학회 2017 International Journal of Control, Automation, and Vol.15 No.5
The unscented Kalman filter (UKF) is a promising approach for the state estimation of nonlinear dynamicsystems due to its simple calculation process and superior performance in highly nonlinear systems. However, itssolution will be degraded or even divergent when the system model involves uncertainty. This paper presents aninteracting multiple model (IMM) estimation-based adaptive robust UKF to address this problem. This methodcombines the merits of the adaptive fading UKF and robust UKF and discards their demerits to inhibit the disturbanceof system model uncertainty on the filtering solution. An adaptive fading UKF for the case of process modeluncertainty and a robust UKF for the case of measurement model uncertainty are established based on the principleof innovation orthogonality. Subsequently, an IMM estimation is developed to fuse the adaptive fading UKF androbust UKF as sub-filters according to the mode probability. The system state estimation is achieved as a probabilisticweighted sum of the estimation results from the two sub-filters. Simulations, experiments and comparisonanalysis validate the efficacy of the proposed method.
Insights into interfacial stability of Li6PS5Cl solid electrolytes with buffer layers
Bingbing Chen,Chaoqun Xu,Han Wang,Jianqiu Zhou 한국물리학회 2019 Current Applied Physics Vol.19 No.2
The large interfacial resistance seriously restricts the development of all-solid-state lithium batteries (ASSLBs). In our work, first-principles calculations are employed to investigate the interfacial properties on lithium (Li) metal anode/Li6PS5Cl solid electrolyte (LPSCl) interface system as well as buffer layers (Li2S) effects. The stable interface structures, Li/LPSCl, L2S/LPSCl and Li/L2S, are established at atomic level. We find that PS4 tetrahedral structure has been seriously destroyed in Li/LPSCl interface, whereas the presence of Li2S buffer layers may smooth the interface without PS4 tetrahedral damage occurred. In addition, the electronic structure of interface indicates that solid electrolyte interphases are not easy to form on LPSCl surfaces considering buffer layers effects, which may improve the stability of anode/solid electrode interface. Moreover, the calculated energies of exchange ions between Li metal and solid electrolyte with buffer layers suggest that the Li2S interposition can suppress the atoms diffusion in LPSCl layers, and provide a smooth interface structure, which may promote the stability of Li/LPSCl interface. This work on the atomic scale will offer a useful perspective for designing high performance of solid electrolytes to enhance good cyclability in ASSLBs.
Multi-sensor Optimal Data Fusion for INS/GNSS/CNS Integration Based on Unscented Kalman Filter
Bingbing Gao,Gaoge Hu,Shesheng Gao,Yongmin Zhong,Chengfan Gu 제어·로봇·시스템학회 2018 International Journal of Control, Automation, and Vol.16 No.1
This paper presents an unscented Kalman filter (UKF) based multi-sensor optimal data fusion methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integration based on nonlinear system model. This methodology is of two-level structure: at the bottom level, the UKF is served as local filters to integrate GNSS and CNS with INS respectively for generating the local optimal state estimates; and at the top level, a novel optimal data fusion approach is derived based on the principle of linear minimum variance for the fusion of local state estimates to obtain the global optimal state estimation. The proposed methodology refrains from the use of covariance upper bound to eliminate the correlation between local states. Its efficacy is verified through simulations, practical experiments and comparison analysis with the existing methods for INS/GNSS/CNS integration.
Bingbing Qiu,Guo-Feng Wang,Yun-Sheng Fan,Dong-Dong Mu,Xiaojie Sun 제어·로봇·시스템학회 2020 International Journal of Control, Automation, and Vol.18 No.8
This paper investigates the path following control problem for underactuated unmanned surface vehicle(USV) in the presence of unmodeled dynamics, external disturbances and input saturation. A novel adaptive robustpath following control scheme is proposed by employing trajectory linearization control (TLC) technology andfinite-time disturbance observer, which is composed of a concise yaw rate controller and a surge speed controller. The salient features of the proposed scheme include: a path following guidance law is designed to ensure USVeffectively converging to and following the desired path; TLC is introduced into the field of USV motion controlas new effective technique, and it is the first time used to design path following controller for underactuated USV;a finite-time nonlinear tracking differentiator is constructed not only to avoid the signal jump caused by derivation,but also to filter noise and high frequency interference. A finite-time disturbance observer (FDO) is devised toexactly observe the uncertain dynamics and unknown external disturbances, which improves the tracking accuracyand precise disturbance rejection of the proposed controller; then, an auxiliary dynamic system that is governed bysmooth switching function is developed to compensate for the saturation constraint on actuator. Stability analysisverifies that all signals in the closed-loop system are uniformly ultimately bounded. Finally, simulation results andcomparisons illustrate the superiority of the proposed control scheme.
sRNA EsrE Is Transcriptionally Regulated by the Ferric Uptake Regulator Fur in Escherichia coli
Bingbing Hou,Xichen Yang,Hui Xia,Haizhen Wu,Jiang Ye,Huizhan Zhang 한국미생물·생명공학회 2020 Journal of microbiology and biotechnology Vol.30 No.1
Small RNAs (sRNAs) are widespread and play major roles in regulation circuits in bacteria. Previously, we have demonstrated that transcription of esrE is under the control of its own promoter. However, the regulatory elements involved in EsrE sRNA expression are still unknown. In this study, we found that different cis-regulatory elements exist in the promoter region of esrE. We then screened and analyzed seven potential corresponding trans-regulatory elements by using pull-down assays based on DNA affinity chromatography. Among these candidate regulators, we investigated the relationship between the ferric uptake regulator (Fur) and the EsrE sRNA. Electrophoresis mobility shift assays (EMSAs) and β-galactosidase activity assays demonstrated that Fur can bind to the promoter region of esrE, and positively regulate EsrE sRNA expression in the presence of Fe2+.
Data Filtering Based Multi-innovation Gradient Identification Methods for Feedback Nonlinear Systems
Bingbing Shen,Feng Ding,Ling Xu,Tasawar Hayat 제어·로봇·시스템학회 2018 International Journal of Control, Automation, and Vol.16 No.5
With the development of industry information technology, many researchers pay attention to the estimation problems of feedback nonlinear systems increasingly. In this paper, a filtering based multi-innovation stochastic gradient algorithm is derived for Hammerstein equation-error autoregressive systems by using the hierarchical technique. The parameter estimates accuracy can be improved with the innovation length increasing. These algorithms are easy to implement on-line. The simulation results verify the effectiveness of the proposed algorithm.