Lijian YIn

Dr. Lijian YIn


Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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24 October 2017 in IEEE Transactions on Systems, Man, and Cybernetics: Systems
Verified
Journal Article
Closed access
LYLijian YIn
Lijian YIn
ZDZhihong Deng
Zhihong Deng
BHBaoyu Huo
Baoyu Huo
YXYuanqing Xia
Yuanqing Xia
A novel adaptive finite-time control method is investigated for the gyros systems in the presence of external disturbance. The fast nonsingular terminal sliding mode surface (NTSMS) is designed which has all advantages of NTSMS and general sliding mode surface together. Based on adaptive law and Lyapunov stability method, the novel proposed theorems are given and proven, and we can obtain that the synchronization errors converge to a small region including zero in finite time. Furthermore, it can be seen that the new adaptive control algorithm can guarantee that the chaotic gyros systems have some excellent properties, and all the signals are finite-time convergent. Finally, the new control scheme is verified by using a numerical example, and can achieve beneficial synchronization under the effectiveness of external disturbance of the gyros systems.

12 March 2020 in IEEE Sensors Journal
Verified
Journal Article
Closed access
ZDZhihong Deng
Zhihong Deng
LSLei Shi
Lei Shi
LYLijian YIn
Lijian YIn
YXYuanqing Xia
Yuanqing Xia
BHBaoyu Huo
Baoyu Huo
Motivated by tracking applications with sensor networks under non-Gaussian noise and intermittent observations, this paper considers a maximum correntropy unscented Kalman filter (MCUKF). MCUKF is based on maximum correntropy criterion (MCC) and unscented transformation (UT) which can deal with both non-Gaussian noise and intermittent observations. The intermittent observations are described by a binary sequence satisfying some properties. The MCC is used to deal with non-Gaussian noise and improves the robustness. Moreover, the arrival probabilities under non-Gaussian noise (shot noise and Gaussian mixture noise) and intermittent observations are given. The performance of the presented algorithm is verified by illustrating numerical examples.

25 February 2024 in Mathematics
Verified
Journal Article
Open access
PDF file
BHBaoyu Huo
Baoyu Huo
MJma jian
ma jian
MDMingjun Du
Mingjun Du
LYLijian YIn
Lijian YIn
This paper studies the average consensus tracking problem of first-order multi-agent systems under directed topologies. A control protocol is constructed based on the neighbors’ agent sampled information. With the help of the matrix theory and frequency domain analysis, the necessary and sufficient condition can be induced for the average consensus tracking of multi-agent systems, although the weight-balanced condition is not satisfied. In addition, a numerical simulation example is given to illustrate the effectiveness of the proposed results.