Jinchuan Zheng

Prof. Jinchuan Zheng

Swinburne University of Technology, Melbourne, Victoria, Australia
orcid

Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

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

Representative Publications

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8 June 2017 in IEEE Transactions on Cybernetics
Verified
Journal Article
Closed access
BNBoda Ning
Boda Ning
QHQing-Long Han
Qing-Long Han
ZZZongyu Zuo
Zongyu Zuo
JJJiong Jin
Jiong Jin
Jinchuan ZhengJinchuan Zheng
Jinchuan Zheng
This paper is concerned with the collective behaviors of robots beyond the nearest neighbor rules, i.e., dispersion and flocking, when robots interact with others by applying an acute angle test (AAT)-based interaction rule. Different from a conventional nearest neighbor rule or its variations, the AAT-based interaction rule allows interactions with some far-neighbors and excludes unnecessary nearest neighbors. The resulting dispersion and flocking hold the advantages of scalability, connectivity, robustness, and effective area coverage. For the dispersion, a spring-like controller is proposed to achieve collision-free coordination. With switching topology, a new fixed-time consensus-based energy function is developed to guarantee the system stability. An upper bound of settling time for energy consensus is obtained, and a uniform time interval is accordingly set so that energy distribution is conducted in a fair manner. For the flocking, based on a class of generalized potential functions taking nonsmooth switching into account, a new controller is proposed to ensure that the same velocity for all robots is eventually reached. A co-optimizing problem is further investigated to accomplish additional tasks, such as enhancing communication performance, while maintaining the collective behaviors of mobile robots. Simulation results are presented to show the effectiveness of the theoretical results.

11 September 2014 in IEEE/ASME Transactions on Mechatronics
Verified
Journal Article
Closed access
Jinchuan ZhengJinchuan Zheng
Jinchuan Zheng
Hai WangHai Wang
Hai Wang
ZMZhihong Man
Zhihong Man
JJJiong Jin
Jiong Jin
MFMinyue Fu
Minyue Fu
A robust motion control system is essential for the linear motor (LM)-based direct drive to provide high speed and high-precision performance. This paper studies a systematic control design method using fast nonsingular terminal sliding mode (FNTSM) for an LM positioner. Compared with the conventional nonsingular terminal sliding mode control, the FNTSM control can guarantee a faster convergence rate of the tracking error in the presence of system uncertainties including payload variations, friction, external disturbances, and measurement noises. Moreover, its control input is inherently continuous, which accordingly avoids the undesired control chattering problem. We further discuss the selection criteria of the controller parameters for the LM to deal with the system dynamic constraints and performance tradeoffs. Finally, we present a robust model-free velocity estimator based on the only available position measurements with quantization noises such that the estimated velocity can be used for feedback signal to the FNTSM controller. Experimental results demonstrate the practical implementation of the FNTSM controller and verify its robustness of more accurate tracking and faster disturbance rejection compared with a conventional NTSM controller and a linear H ∞ controller.

28 August 2019 in IEEE Transactions on Industrial Electronics
Verified
Journal Article
Closed access
Ke ShaoKe Shao
Ke Shao
Jinchuan ZhengJinchuan Zheng
Jinchuan Zheng
KHKang Huang
Kang Huang
Hai WangHai Wang
Hai Wang
ZMZhihong Man
Zhihong Man
MFMinyue Fu
Minyue Fu
Payload variations, friction, and external disturbances deteriorate the control performance of linear motor (LM) positioners. To provide high-speed and high-precision performance for the LM, an adaptive recursive terminal sliding mode (ARTSM) controller is proposed in this paper. For the controller, a fast nonsingular terminal sliding function and a recursive integral terminal sliding function are developed in a recursive structure such that the sliding surfaces are arrived successively and ultimately the tracking error can converge to zero in a finite time. Furthermore, by setting an appropriate initial value for the integral element of the ARTSM controller, the control system is enforced to start on the sliding surface at the initial time such that the reaching time is reduced. Stability analysis is presented to prove the finite-time convergence and zero tracking error of the closed-loop system under the proposed ARTSM controller. Experiment results also demonstrate the effectiveness of the controller in term of significantly reduced tracking errors and faster disturbance rejection in comparison with a recently reported fast nonsingular terminal sliding mode (FNTSM) controller for the LM positioner.

9 February 2021 in IEEE Transactions on Industrial Electronics
Verified
Journal Article
Closed access
SLShikang Lian
Shikang Lian
WMWei Meng
Wei Meng
Zemin LinZemin Lin
Zemin Lin
Ke ShaoKe Shao
Ke Shao
Jinchuan ZhengJinchuan Zheng
Jinchuan Zheng
RLRenquan Lu
Renquan Lu
As one type of unmanned aerial vehicles, the quadrotor typically suffers from payload variations, system uncertainties, and environmental wind disturbances, which significantly deteriorate its attitude control performance. To provide high-speed, accurate, and robust attitude tracking performance for the quadrotor, an adaptive fast nonsingular terminal sliding mode (AFNTSM) controller is proposed in this article. The proposed AFNTSM controller combines the advantages of fast nonsingular terminal sliding mode (FNTSM), integral sliding mode, and adaptive estimation techniques, which are effective to achieve the desired tracking performance and suppress control signal chattering. Furthermore, unlike conventional methods, the adaptive estimation removes the requirements for the upper bound information of the disturbances. It is proved that the proposed AFNTSM can guarantee finite-time convergence and zero tracking error for the quadrotor attitude control. Finally, comparative study with the FNTSM control only and conventional sliding mode control is conducted through experiments and the results demonstrate that the proposed AFNTSM can achieve faster convergence and stronger robustness in line with theoretical analysis.

23 January 2018 in IEEE Transactions on Industrial Electronics
Verified
Journal Article
Closed access
Hai WangHai Wang
Hai Wang
LSLiheng Shi
Liheng Shi
ZMZhihong Man
Zhihong Man
Jinchuan ZhengJinchuan Zheng
Jinchuan Zheng
SLShihua Li
Shihua Li
ZCZhenwei Cao
Zhenwei Cao
The control of automobile electronic throttle (AET) systems is a challenging task owing to multiple nonlinearities, i.e., transmission friction, gear backlash, limp-home spring set, and external load disturbance. In this paper, a practical tracking control scheme of an AET system is developed using a continuous fast nonsingular terminal sliding mode (CFNTSM) technique based on uncertainty observer. By using the prescribed CFNTSM surface and fast terminal sliding mode-based reaching element, the proposed control implementation guarantees the fast error convergence characteristic and high tracking accuracy under parameter uncertainties and perturbations. Furthermore, due to the adoption of the finite-time exact observer (FEO) for the lumped uncertainty estimation in the controller, the ease of the selection of the control gains is well-achieved since they only depend on the uncertainty estimation error. The closed-loop stability and finite-time convergence are presented based on the Lyapunov stability theory. Experimental verifications are conducted to validate the remarkable performance of the proposed control, in terms of the step and sinusoidal tracking as well as anti-disturbance ability.

1 January 2021 in Mechanical Systems and Signal Processing
Verified
Journal Article
Closed access
Ke ShaoKe Shao
Ke Shao
Jinchuan ZhengJinchuan Zheng
Jinchuan Zheng
HWHai Wang
Hai Wang
FXFeng Xu
Feng Xu
XWXueqian Wang
Xueqian Wang
BLBin Liang
Bin Liang