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Adaptive Time-varying Sliding Surface for Second-Order Variable Structure Control
Zhiping Zhu,Kui Yuan,Huosheng Hu 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
This paper introduces an adaptive time-varying sliding surface for the second order variable structure controlsystem which can improve the robustness of the control system by shortening the reaching phase. A saturation functionis adopted to replace the conventional sign function in the controller to decrease the switching frequency of the sliding control action and thus to reduce the chattering of the system.
Robust Stability Analysis of an Uncertain Nonlinear Networked Control System Category
Minrui Fei,Jun Yi,Huosheng Hu 대한전기학회 2006 International Journal of Control, Automation, and Vol.4 No.2
In the networked control system (NCS), the uncertain network-induced delay and nonlinear controlled object are the main problems, because they can degrade the performance of the control system and even destabilize it. In this paper, a class of uncertain and nonlinear networked control systems is discussed and its sufficient condition for the robust asymptotic stability is presented. Further, the maximum network-induced delay that insures the system stability is obtained. The Lyapunov and LMI theorems are employed to investigate the problem. The result of an illustrative example shows that the robust stability analysis is sufficient.
An Improved Harris-SIFT Algorithm Based on Rotation-invariant LBP Operator
Lei Yang,Yanyun Ren,Jiyuan Cai,Huosheng Hu 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.6
Feature-points matching is an important concept in binocular stereo vision. The procession of multi-scale feature-points matching in classical Harris-SIFT algorithm is time-consuming and has high complexity when describing the feature-points. This paper proposed a new improved Harris-SIFT algorithm based on rotation-invariant LBP (Local binary patterns) operator. Firstly, the Harris operator is used to extract feature points from DOG (Difference of Gaussian) scale space. Then, the dominant direction of feature point is calculated and 81-dimensional rotation-invariant LBP descriptors are extracted when the rotation matching window is coordinated to this direction. At last, Best-Bin-First (BBF) algorithm is used to search the matching points between the two sets of feature points. Experimental results show that the proposed algorithm is lower time-consuming than classical Harris-SIFT algorithm and remains the similar matching correct rate.
A novel data-driven rollover risk assessment for articulated steering vehicles using RNN
Xuanwei Chen,Wei Chen,Liang Hou,Huosheng Hu,Xiangjian Bu,Qingyuan Zhu 대한기계학회 2020 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.34 No.5
Articulated steering vehicles have outstanding capability operating but suffer from frequent rollover accidents due to their complicated structure. It is necessary to accurately detect their rollover risk for drivers to take action in time. Their variable structure and the variable center of mass exhibit nonlinear time-variant behavior and increase the difficulty of dynamic modelling and lateral stability description. This paper proposes a novel data-driven modelling methodology for lateral stability description of articulated steering vehicles. The running data is first collected based on the typical operations that prone to rollover and then classified into two types: Safety and danger. The data quality is further improved by wavelet transformation. Finally, an RNN model is built on the data. The experimental results show that the output of the RNN model can accurately quantify lateral stability of the vehicle, i.e., the risk of rollover, when it is turning and crossing uneven surfaces or obstacles.