Article
Computer Science, Information Systems
Lubna Khasawneh, Manohar Das
Summary: This paper addresses the challenges associated with steering-angle control of electric power steering for autonomous vehicles. It proposes a variable gain-sliding mode steering-angle controller and develops a sliding mode observer to estimate the self-aligning moment disturbance and other disturbances. Simulation and experimental results demonstrate the stability and robustness of the proposed methods to the challenges mentioned.
Article
Engineering, Civil
Jinghua Guo, Wenchang Li, Jingyao Wang, Yugong Luo, Keqiang Li
Summary: This paper proposes an adaptive cruise control framework considering regenerative braking to improve safety and energy efficiency of IEVs during the car-following process. The framework includes a coupled and nonlinear dynamic model of IEVs system, an adaptive fuzzy sliding mode high-level controller, and traction control, brake control, and a regenerative braking strategy in the lower-level controller. Simulation results demonstrate excellent performance in longitudinal tracking and braking energy recovery without safety loss.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Computer Science, Interdisciplinary Applications
Te Chen, Yingfeng Cai, Long Chen, Xing Xu, Xiaoqiang Sun
Summary: This study focuses on the trajectory tracking control problem of steer-by-wire autonomous ground vehicles in the event of complete failure of the vehicle steering motor. By analyzing the mechanical transmission mechanism and designing controllers, the study successfully demonstrates the use of differential steering for vehicle turning in emergencies, and proposes an observer design method to estimate the actual vehicle steering angle.
SIMULATION MODELLING PRACTICE AND THEORY
(2021)
Article
Engineering, Mechanical
Jinghua Guo, Keqiang Li, Jingjing Fan, Yugong Luo, Jingyao Wang
Summary: This paper proposes a novel neural-fuzzy-based adaptive sliding mode automatic steering control strategy for improving the driving performance of vision-based unmanned electric vehicles. The system utilizes neural network and fuzzy inference system for monitoring the automatic steering of vehicles. The results indicate that the control scheme performs well in terms of error convergence and robustness.
CHINESE JOURNAL OF MECHANICAL ENGINEERING
(2021)
Article
Automation & Control Systems
Alejandra Hernandez-Sanchez, Olga Andrianova, Alexander Poznyak, Isaac Chairez
Summary: The paper introduces a state feedback and robust controller design for regulating the tridimensional movement of autonomous underwater mobile crafts (AUMCs) using Averaged Sub-Gradient Integral Sliding Mode Realisation (ASGISMR). This design successfully handles tracking error and enables AUMCs to maintain continuous movement underwater.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2021)
Article
Engineering, Mechanical
Wenfei Li, Huiyun Li, Chao Huang, Kun Xu, Tianfu Sun, Haiping Du
Summary: The study presents a coordinated control system for blended braking systems, which effectively addresses the challenges posed by braking actuator time-delay and unmeasurable states, leading to improved braking performance.
Article
Engineering, Mechanical
Ali Barari, Sajad Saraygord Afshari, Xihui Liang
Summary: This paper proposes a coordinated control strategy to improve the path-following capability of autonomous four in-wheel motor drive electric vehicles. By combining self-tunable super-twisting sliding mode control and model predictive control, parametric uncertainties are handled, and control action is allocated to active front steering and direct yaw moment control. Simulation results demonstrate that the proposed controller outperforms the MPC controller in path-following.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE
(2022)
Article
Engineering, Civil
Yan Yan, Haiping Du, Yafei Wang, Weihua Li
Summary: The platoon of connected autonomous vehicles plays a crucial role in future intelligent transportation by improving traffic efficiency and alleviating congestion. This paper proposes a multi-objective asymmetric sliding mode control strategy to address the challenging problems of control in connected autonomous vehicles. The results demonstrate that the proposed control strategy enhances stability and performance of the platoon.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Mechanical
Chen Ding, Shihong Ding, Xinhua Wei, Keqi Mei
Summary: This paper develops output feedback sliding mode control methods for the path-tracking control system of autonomous agricultural vehicles. By introducing coordinate transformation and using second-order robust exact differentiator, the path-tracking control is achieved. Traditional first-order sliding mode control and second-order sliding mode control are employed to improve the precision and transient performance of the path-tracking.
NONLINEAR DYNAMICS
(2022)
Review
Engineering, Mechanical
Qingyong Zhang, Mingjun Jiang, Yiqing Yuan, Zhen Fan, Shanyou Chen
Summary: This paper studies a method for front and rear axle braking force distribution, using the actual road adhesion coefficient and braking strength as premise to distribute the front axle electromechanical braking force, and enhancing the stability of the anti-lock system using fuzzy control. Finally, a braking coordination control strategy is proposed, combining the regenerative braking and anti-lock control, which has been proven effective in improving the economy of pure electric vehicles through simulations and experiments.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING
(2022)
Article
Automation & Control Systems
Yongpeng Weng, Ning Wang
Summary: This paper investigates the problem of robust tracking control of disturbed unknown autonomous surface vehicles (ASVs). A sliding-mode-control-based model-free tracking control (SMTC) approach is proposed, which combines sliding-mode control and data-driven backstepping techniques. The approach includes a data-driven adaptive controller and a data-driven adaptive law for estimating unknowns. The proposed SMTC approach achieves strong adaptability and robustness to unknown couplings, uncertainties, and disturbances, and guarantees asymptotic tracking performance and strong robustness theoretically. Simulation studies demonstrate the validity and superiority of the SMTC approach in terms of disturbance attenuation, nonlinearity adaption, and high accurate tracking.
Article
Automation & Control Systems
Cheng Zhu, Bing Huang, Bin Zhou, Yumin Su, Enhua Zhang
Summary: This paper presents a model-parameter-free control strategy for the trajectory tracking problem of autonomous underwater vehicles, using two control architectures to achieve desired trajectories with improved system reliability under actuator failures. The proposed controllers leverage sliding mode control technology and adaptive algorithms to handle nonlinear dynamics of underwater vehicles, demonstrating validity through theoretical analysis and numerical simulations.
Article
Mathematics
Jiajian Liang, Wenkai Huang, Fobao Zhou, Jiaqiao Liang, Guojian Lin, Endong Xiao, Hongquan Li, Xiaolin Zhang
Summary: This paper proposes a double-loop proportional-integral-differential neural network sliding mode control method to eliminate the influence of nonlinear disturbances on the trajectory tracking of autonomous underwater vehicles. Experimental results demonstrate its strong anti-jamming ability and tracking performance.
Article
Automation & Control Systems
Hongde Qin, Jinshuai Si, Ning Wang, Liyang Gao, Kangjian Shao
Summary: This paper presents a novel disturbance estimator-based fast fuzzy terminal sliding-mode formation control method. The leader-follower formation control method is combined with path planning strategy based on artificial potential field to ensure collision-free and consensus movement for each AUV. An improved sliding-mode surface is incorporated into the controller for faster convergence rate away from the stable equilibrium. Fuzzy control rules derived from the Lyapunov energy function are designed to eliminate the chattering problem in the controller. A disturbance estimator is proposed to compensate for unknown dynamics and disturbances, enhancing the system's robustness and stability. Simulation and comparison results are provided to demonstrate the effectiveness of the proposed method.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2023)
Article
Automation & Control Systems
Fanbiao Li, Zheng Wu, Nikhil R. Pal, Chunhua Yang, Hao Peng, Okyay Kaynak, Tingwen Huang
Summary: This article presents an adaptive control strategy for the lane-keeping task of automatic steering systems using sliding-mode technique. It employs interval type-2 fuzzy sets to reconstruct the steering system dynamics model and proposes an integral sliding surface for improved tracking capability and robustness to unknown disturbances.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
