Lizhe Wu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Lizhe Wu has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Dingxuan Zhao
Yanshan University
3 shared publications - Xiaolong Zhao
School of Mechanical Engineering, Yanshan University, Qinhuangdao 066004, China
1 shared publication - Yalu Qin
School of Mechanical Engineering and the State Key Laboratory of Crane Technology, Yanshan University, Qinhuangdao, China
1 shared publication - Zhenhua Liu
Department of Mechanical Engineering, Hebei University of Water Resources and Electric Engineering, Cangzhou 061001, China
1 shared publication
Latest Publications
- Open Access
- 8 April 2025
- Published by MDPI AG in Mathematics
- Vol. 13 (8) , 1217
Control of Vehicle Lateral Handling Stability Considering Time-Varying Full-State Constraints
Lateral handling stability control is crucial for ensuring vehicle driving safety. To address this issue, this paper proposes a lateral handling stability control method that considers time-varying full-state constraints. By constructing a time-varying symmetric Barrier Lyapunov Function (TS-BLF), this method imposes time-varying nonlinear constraints on both the sideslip angle and yaw rate, thereby ensuring full-state constrained stability control of vehicles under complex operating conditions. Additionally, a second-order command filtering technique with an error compensation mechanism is introduced to reduce the computational complexity of control laws while mitigating filter-induced errors that may degrade system performance. To validate the effectiveness and robustness of the proposed method, the vehicle’s dynamic response is analyzed under different speeds on both dry asphalt pavement and dry gravel surfaces. The simulation results demonstrate that the proposed method effectively suppresses understeer and oversteer, enhances the dynamic stability margin under extreme operating conditions, and improves vehicle adaptability in complex environments.
- 8 April 2025
- Published by MDPI AG in Mathematics
- Vol. 13 (8) , 1217
Open AccessControl of Vehicle Lateral Handling Stability Considering Time-Varying Full-State Constraints
Lateral handling stability control is crucial for ensuring vehicle driving safety. To address this issue, this paper proposes a lateral handling stability control method that considers time-varying full-state constraints. By constructing a time-varying symmetric Barrier Lyapunov Function (TS-BLF), this method imposes time-varying nonlinear constraints on both the sideslip angle and yaw rate, thereby ensuring full-state constrained stability control of vehicles under complex operating conditions. Additionally, a second-order command filtering technique with an error compensation mechanism is introduced to reduce the computational complexity of control laws while mitigating filter-induced errors that may degrade system performance. To validate the effectiveness and robustness of the proposed method, the vehicle’s dynamic response is analyzed under different speeds on both dry asphalt pavement and dry gravel surfaces. The simulation results demonstrate that the proposed method effectively suppresses understeer and oversteer, enhances the dynamic stability margin under extreme operating conditions, and improves vehicle adaptability in complex environments.
- Open Access
Command-Filtered Yaw Stability Control of Vehicles with State Constraints
Yaw stability control is crucial for ensuring the driving safety of intelligent vehicles. This paper proposes a state-constrained command-filtered control (CFC) approach for vehicle yaw stability. The proposed method employs a barrier Lyapunov function (BLF) to effectively constrain the vehicle’s sideslip angle and yaw rate, thereby enhancing system stability and safety. Meanwhile, a command-filtered control strategy is introduced to reduce computational complexity, and an error compensation mechanism is incorporated to mitigate the adverse effects of filter-induced errors on system performance. To validate the effectiveness and robustness of the proposed method, simulations are conducted under different road adhesion conditions and driving speeds. The results demonstrate that the proposed control approach effectively suppresses both understeer and oversteer phenomena, significantly improving vehicle handling stability. This study provides theoretical support and practical insights for the engineering application of yaw stability control in intelligent vehicles.
Open AccessCommand-Filtered Yaw Stability Control of Vehicles with State Constraints
Yaw stability control is crucial for ensuring the driving safety of intelligent vehicles. This paper proposes a state-constrained command-filtered control (CFC) approach for vehicle yaw stability. The proposed method employs a barrier Lyapunov function (BLF) to effectively constrain the vehicle’s sideslip angle and yaw rate, thereby enhancing system stability and safety. Meanwhile, a command-filtered control strategy is introduced to reduce computational complexity, and an error compensation mechanism is incorporated to mitigate the adverse effects of filter-induced errors on system performance. To validate the effectiveness and robustness of the proposed method, simulations are conducted under different road adhesion conditions and driving speeds. The results demonstrate that the proposed control approach effectively suppresses both understeer and oversteer phenomena, significantly improving vehicle handling stability. This study provides theoretical support and practical insights for the engineering application of yaw stability control in intelligent vehicles.
- Open Access
Nonlinear Adaptive Back-Stepping Optimization Control of the Hydraulic Active Suspension Actuator
The displacement tracking performance of the electro-hydraulic servo actuator is critical for hydraulic active suspension control. To tackle the problem of slow time-varying parameters in the existing actuator dynamics model, a nonlinear adaptive back-stepping control (ABC) approach is adopted. Simultaneously, the parameters of the nonlinear ABC are difficult to configure, resulting in a poor control effect. An enhanced particle swarm optimization (PSO) approach integrating crazy particles (CP) and time-varying acceleration coefficients (TVAC) is suggested to optimize the controller settings. Furthermore, in order to obtain satisfactory dynamic characteristics of the transition process, the absolute value of the error time integral performance index is used as the minimum performance index function of parameter selection, and the square term of the control input is added to the performance index function to prevent excessive controller energy. Finally, it can be observed from the simulation results of the highest value of the displacement tracking error, the average value of error, and the standard deviation of error that the performance of the ABC parameters optimized by PSO+CP+ATVC is superior to the manually given ABC parameters. Therefore, this control method significantly improves the stability and speed of the control system. It provides a new research idea for the parameter optimization of controllers.Open AccessNonlinear Adaptive Back-Stepping Optimization Control of the Hydraulic Active Suspension Actuator
The displacement tracking performance of the electro-hydraulic servo actuator is critical for hydraulic active suspension control. To tackle the problem of slow time-varying parameters in the existing actuator dynamics model, a nonlinear adaptive back-stepping control (ABC) approach is adopted. Simultaneously, the parameters of the nonlinear ABC are difficult to configure, resulting in a poor control effect. An enhanced particle swarm optimization (PSO) approach integrating crazy particles (CP) and time-varying acceleration coefficients (TVAC) is suggested to optimize the controller settings. Furthermore, in order to obtain satisfactory dynamic characteristics of the transition process, the absolute value of the error time integral performance index is used as the minimum performance index function of parameter selection, and the square term of the control input is added to the performance index function to prevent excessive controller energy. Finally, it can be observed from the simulation results of the highest value of the displacement tracking error, the average value of error, and the standard deviation of error that the performance of the ABC parameters optimized by PSO+CP+ATVC is superior to the manually given ABC parameters. Therefore, this control method significantly improves the stability and speed of the control system. It provides a new research idea for the parameter optimization of controllers.