Yang Liu

Dr. Yang Liu


Research Focus & Metrics

Academic Career Length

19Years (2008-Present)

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

Representative Publications

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20 August 2018 in IEEE Transactions on Fuzzy Systems
Verified
Journal Article
Closed access
YLYang Liu
Yang Liu
Xiaoping LiuXiaoping Liu
Xiaoping Liu
YYYuanwei YuanJing
Yuanwei YuanJing
ZZZiye Zhang
Ziye Zhang
This work investigates a finite-time adaptive fuzzy tracking control problem for a class of non-strict feedback nonlinear systems from a new point of view. A new concept, named Finite-Time Performance Function (FTPF), is defined in this paper for the first time. Moreover, a finite-time adaptive state feedback fuzzy tracking controller is derived based on fuzzy approximation, backstepping technique and Prescribed Performance Control (PPC), which guarantees that all the signals of the closed-loop system are bounded, the output tracking error converges to a prescribed arbitrarily small region within a finite-time interval, and maximum overshoot is not more than a predefined level. In addition, a controller design process is given, which is less complex than the existing finite-time control design methods. Three simulation studies are provided to verify the feasibility and effectiveness of the theoretical finding in this study.

1 November 2018 in Information Sciences
Verified
Journal Article
Closed access
YLYang Liu
Yang Liu
XLXiaoping Liu
Xiaoping Liu
YJYuanwei Jing
Yuanwei Jing

10 October 2022 in IEEE Transactions on Neural Networks and Learning Systems
Verified
Journal Article
Closed access
LCLiang Cao
Liang Cao
ZCZhijian Cheng
Zhijian Cheng
YLYang Liu
Yang Liu
HLHongyi Li
Hongyi Li
This article focuses on the fixed-time formation control problem for nonlinear multiagent systems (MASs) with dynamic uncertainties and limited communication resources. Under the framework of the backstepping method, a time-varying formation function is introduced in the controller design. To attain the prescribed transient and steady-state performance of MASs, a fixed-time prescribed performance function (FTPPF) is designed and the further coordinate transformation addressing the zero equilibrium point problem is removed. To achieve better approximating performance, a neural network (NN)-based composite dynamic surface control (CDSC) strategy is proposed, where the CDSC scheme is consisted of prediction errors and serial–parallel estimation models. According to the signals generated by the estimation models, disturbance observers are established to overcome the difficulty from approximating errors and mismatched disturbances. Moreover, an improved dynamic event-triggered mechanism and varying threshold parameters are constructed to reduce the signal transmission frequency. Via the Lyapunov stability theory, all the signals in the closed-loop system are semi-globally uniformly ultimately bounded. Finally, the simulation results verify the effectiveness of the developed CDSC strategy.

10 June 2022 in IEEE Transactions on Systems, Man, and Cybernetics: Systems
Verified
Journal Article
Closed access
YLYang Liu
Yang Liu
DYDeyin Yao
Deyin Yao
LWLijie Wang
Lijie Wang
SLShejie Lu
Shejie Lu
This article focuses on the distributed adaptive fixed-time platoon tracking problem for third-order fully heterogeneous nonlinear vehicles. The modified dynamics of each vehicle are constructed, and a practically fixed-time criterion is set up. Moreover, the singularity problem in the fixed-time and finite-time control is addressed well by designing new virtual signals and exploiting the inequality technique and power transformation scheme instead of the approximation method. The distributed nonlinear fixed-time tracking protocol is constructed by virtue of the recursive algorithm, and the design process is simplified by a tracking differentiator. In particular, the upper bound of the settling time has nothing to do with initial conditions. Further, the disturbances are tackled via robust $H_{\infty }$ control theory. Finally, simulation tests are contained to illustrate the performance of the proposed protocols.

24 June 2019 in IEEE Transactions on Neural Networks and Learning Systems
Verified
Journal Article
Closed access
YLYang Liu
Yang Liu
Xiaoping LiuXiaoping Liu
Xiaoping Liu
YYYuanwei YuanJing
Yuanwei YuanJing
XCXiangyong Chen
Xiangyong Chen
JQJianlong Qiu
Jianlong Qiu
This paper investigates an adaptive finite-time control (FTC) problem for a class of strict-feedback nonlinear systems with both time-delays and quantized input from a new point of view. First, a new concept, called preassigned finite-time performance function (PFTF), is defined. Then, another novel notion, called practically preassigned finite-time stability (PPFTS), is introduced. With PFTF and PPFTS in hand, a novel sufficient condition of the FTC is given by using the neural network (NN) control and direct adaptive backstepping technique, which is different from the existing results. In addition, a modified barrier function is first introduced in this work. Moreover, this work is first to focus on the FTC for the situation that the time-delay and quantized input simultaneously exist in the nonlinear systems. Finally, simulation results are carried out to illustrate the effectiveness of the proposed scheme.

6 January 2020 in IEEE Transactions on Systems, Man, and Cybernetics: Systems
Verified
Journal Article
Closed access
YLYang Liu
Yang Liu
Xiaoping LiuXiaoping Liu
Xiaoping Liu
YYYuanwei YuanJing
Yuanwei YuanJing
HWHuanqing Wang
Huanqing Wang
XLXiaohua Li
Xiaohua Li
This article focuses on an annular domain finite-time connectively bounded (ADFTCB) problem for a large-scale system with expanding construction (LSWEC). The LSWEC is built via adding new subsystems into the original system which is operating. Inspired by the notion of finite-time annular domain stability (FTADS), a new concept, ADFTCB, is presented in this article, and it is extended to LSWEC for the first time. First of all, the mathematical models of LSWEC and LSWEC with observer are built, and then the corresponding decentralized state-feedback stabilizers and output-feedback stabilizers with observers are designed with the aid of finite-time Lyapunov theory and linear matrix inequality (LMI) method which can make the closed-loop system ADFTCB. A simulation study is provided to demonstrate the feasibility and effectiveness of the presented strategy.