Minghui Ou

Prof. Dr. Minghui Ou

Chongqing Vocational Institute of Engineering, Chongqing, China
+1
orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

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

Representative Publications

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1 January 2021 in International Journal of Electrical Power & Energy Systems
Verified
Journal Article
Closed access
HZHao Zhang
Hao Zhang
SLShan Liang
Shan Liang
MOMinghui Ou
Minghui Ou
MWMengli Wei
Mengli Wei

2 January 2023 in World Electric Vehicle Journal
Verified
Journal Article
Open access
PDF file
MCMengyuan Chen
Mengyuan Chen
YRYue Ren
Yue Ren
MOMinghui Ou
Minghui Ou
As the bottom layer of the autonomous vehicle, path tracking control is a crucial element that provides accurate control command to the X-by-wire chassis and guarantees the vehicle safety. To overcome the deterioration of control performance for autonomous vehicle path-tracking controllers caused by modeling errors and parameter perturbation, an adaptive robust control framework is proposed in this paper. Firstly, the 2-DOF vehicle dynamic model is established and the non-singular fast terminal sliding mode control algorithm is adopted to formulate the control law. The unmeasured model disturbance and parameter perturbation is regarded as the system uncertainty. To enhance the control accuracy, the radial basis forward neural network is introduced to estimate such uncertainty in real time. Then, the dynamic model of an active front steering system is established. The model reference control algorithm is applied for the steering torque control considering model uncertainty brought by the dissipation of manufacturing and mechanical wear. Finally, the Simulink–CarSim co-simulation platform is used and the proposed control framework is validated in two test scenarios. The simulation results demonstrate the proposed adaptive robust control algorithm has satisfactory control performance and good robustness against the system uncertainty.

1 August 2019 in Applied Mathematics and Computation
Verified
Journal Article
Closed access
MOMinghui Ou
Minghui Ou
LSLiang Shan
Liang Shan
CZCheng Zeng
Cheng Zeng
1

6 May 2019 in International Journal of Control, Automation, and Systems
Verified
Journal Article
Closed access
PDF file
MOMinghui Ou
Minghui Ou
LSLiang Shan
Liang Shan
CZCheng Zeng
Cheng Zeng

1 January 2020 in IFAC-PapersOnLine
Verified
Journal Article
Closed access
MOMinghui Ou
Minghui Ou
SLShan Liang
Shan Liang
HZHao Zhang
Hao Zhang
TLTong Liu
Tong Liu
JLJing Liang
Jing Liang

1 December 2017
Verified
Conference Paper
Closed access
MOMinghui Ou
Minghui Ou
SLShan Liang
Shan Liang
TLTong Liu
Tong Liu
CZCheng Zeng
Cheng Zeng
The paper investigates the stability of zero dynamics of the exact sampled data systems composed of a backward triangle sampled and hold (BTSH), a continuous-time multivariable plant and a sampler in cascade. Then a new zero dynamics polynomials is established and it can reflect the relationship of zeros between general linear continuous time systems and the exact sampled data systems. The properties of the limiting zeros are studied and the stability conditions of limiting zeros of exact sampled data systems for sufficiently small sampling periods are derived. We show that the zero dynamics of the discrete time systems can be stabilized by selecting proper parameters of the BTSH. Simulation results are provided to show the good performance and stabilization of the corresponding zero dynamics.