12 results on '"Yin, Guodong"'
Search Results
2. Stochastic Stable Control of Vehicular Platoon Time-Delay System Subject to Random Switching Topologies and Disturbances.
- Author
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Xu, Liwei, Jin, Xianjian, Wang, Yan, Liu, Ying, Zhuang, Weichao, and Yin, Guodong
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ELECTRIC vehicles ,AIR resistance ,MARKOVIAN jump linear systems ,SYSTEMS theory ,STABILITY theory ,HYPERSONIC planes - Abstract
This paper presents a stochastic stable control protocol for heterogeneous vehicle platoon subject to communication topologies change, external disturbance, and information delay. First, a random vehicle platoon system composed entirely of several pure electric vehicles is built. The random variation of data transmission link among the platoon in a natural traffic environment is considered and molded by the Markov chain combined with the directed graph method. The influence of delays and discrete data in wireless communication, road slope, and air resistance on the vehicle platoon is also considered by introducing the external interferences and equivalent information delays. Additionally, to ensure the vehicle platoon’s inner-vehicle stability, the variable-gain distributed controller is proposed based on the Markovian jumping system stability theory and $ H_\infty$ control. Finally, the $ \mathcal {L}_{2}$ stochastic string stability is defined to attenuate perturbations as they propagate through the platoon. Simulation studies about a vehicle platoon under four communication topologies random switching with two different control methods are provided to verify the theoretical result. It is shown that, compared to traditional platoon robust control, it is possible to achieve the vehicle platoon’s stability even if in the continuous mutation of unstable topologies by using the proposed control approach. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
3. Path Planning on Large Curvature Roads Using Driver-Vehicle-Road System Based on the Kinematic Vehicle Model.
- Author
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Wang, Jinxiang, Yan, Yongjun, Zhang, Kuoran, Chen, Yimin, Cao, Mingcong, and Yin, Guodong
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VEHICLE models ,CURVATURE ,AUTONOMOUS vehicles ,TRAFFIC safety ,ENVIRONMENTAL security ,ROADS - Abstract
Path planning is a critical part for improving the driving safety and driver comfort of autonomous vehicles (AVs), especially in complex maneuvering conditions. In addition, different drivers have different preferences for AVs, thus, how to provide personalized trajectories for different drivers is a vital issue for AVs. The collision-free path planning problem in conditions with large road curvatures is investigated in this paper, with the consideration of environmental safety constraints, drivers’ comfort, vehicle actuator constraints, etc. Firstly, a Driver-Vehicle-Road (DVR) system is established based on the combination of the kinematic vehicle model and the two-point visual preview driver model, such that the driver's individual handling characteristics can be considered in the controller. The kinematic vehicle model is modified to have the similar understeering characteristics with those of the nonlinear full car models, and then the proposed DVR system can satisfy different groups of drivers and cars. Secondly, for environmental constraints, a new artificial potential field (APF) method is proposed, which can form a banana-shaped 3-D dangerous imaginary mountain and a lane boundary cliff suitable for arbitrary curvature roads to generate a collision-free evasive path. Finally, the Linear-Time-Varying (LTV) model predictive control (MPC) method is adopted to design the path planner. The CarSim-Simulink joint simulation illustrates that with the proposed planner, the host vehicle is capable of avoiding obstacles with a safer and more comfortable maneuver on large curvature roads. And the proposed path planner can provide individually safe trajectories for different drivers with good maneuverability. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
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4. Geometry-Based Cooperative Localization for Connected Vehicle Subject to Temporary Loss of GNSS Signals.
- Author
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Wang, Fa'an, Xu, Liwei, Zhuang, Weichao, Yin, Guodong, Pi, Dawei, Liang, Jinhao, Liu, Ying, and Lu, Yanbo
- Abstract
Onboard GNSS signal loss is a challenging issue for automated vehicles during driving in urban areas due to the effects of tall and dense buildings, flyovers, tunnels, and vegetation. To improve the vehicle localization accuracy when GNSS signals temporarily lost, this paper proposes a Geometry-based cooperative localization method (GCL) for the Internet of Vehicles. The vehicle position is estimated using mathematical geometry information, including vehicle dynamics and road shapes, which could reduce the environment-aware position constraint of cooperative localization. The relocation approach is enabled by communicating with neighboring vehicles to attenuate GNSS signal loss on localization-based services. The efficiency and scalability of GCL are evaluated in different driving conditions. The results showed that GCL achieved better localization performance than the state-of-the-art techniques in shorter and longer GNSS signal loss situations. The experimental results demonstrated the capabilities and effectiveness of the proposed algorithm to handle typical GNSS signal loss driving scenarios. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
5. Enhanced Eco-Approach Control of Connected Electric Vehicles at Signalized Intersection With Queue Discharge Prediction.
- Author
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Dong, Haoxuan, Zhuang, Weichao, Chen, Boli, Yin, Guodong, and Wang, Yan
- Subjects
SIGNALIZED intersections ,ELECTRIC vehicles ,DYNAMIC programming ,ENERGY consumption ,FORECASTING - Abstract
Long queues of vehicles are often found at signalized intersections, which increases the energy consumption of all the vehicles involved. This paper proposes an enhanced eco-approach control (EEAC) strategy with consideration of the queue ahead for connected electric vehicles (EVs) at a signalized intersection. The discharge movement of the vehicle queue is predicted by an improved queue discharge prediction method (IQDP), which takes both vehicle and driver dynamics into account. Based on the prediction of the queue, the EEAC strategy is designed with a hierarchical framework: the upper-stage uses dynamic programming to find the general trend of the energy-efficient speed profile, which is followed by the lower-stage model predictive controller to computes the explicit solution for a short horizon with guaranteed safe inter-vehicular distance. Finally, numerical simulations are conducted to demonstrate the energy efficiency improvement of the EEAC strategy. Besides, the effects of the queue prediction accuracy on the performance of the EEAC strategy are also investigated. [ABSTRACT FROM AUTHOR]
- Published
- 2021
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6. A Distributed Integrated Control Architecture of AFS and DYC Based on MAS for Distributed Drive Electric Vehicles.
- Author
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Liang, Jinhao, Lu, Yanbo, Yin, Guodong, Fang, Zhenwu, Zhuang, Weichao, Ren, Yanjun, Xu, Liwei, and Li, Yanjun
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ELECTRIC drives ,OPTIMAL control theory ,MOTOR vehicle driving ,MULTIAGENT systems ,COST functions - Abstract
Reconstitution of control architecture creates a great challenge for distributed drive electric vehicles (DDEV), due to the emergence of a new distributed driving strategy. To this end, a novel distributed control architecture is proposed in this paper for integrated control of active front steering (AFS) system and direct yaw moment (DYC) system. First, a multi-agent system (MAS) is employed to construct a general framework, where AFS and DYC act as agents that work together to improve vehicle lateral stability and simultaneously reduce workloads of drivers during path tracking. The cooperative control strategies of two agents are obtained through Pareto-optimality theory to ensure optimal control performance of AFS and DYC. Then, on the basis of dynamic interaction between agents, terminal constraints, including terminal cost function and terminal input with local static feedback, are designed to guarantee the asymptotic stability of the close-loop system. Finally, virtual simulations are conducted to evaluate the proposed controller. The results indicate that the proposed control architecture can effectively preserve vehicle stability and reduce workloads of drivers, especially for the inexperienced driver. Furthermore, the hardware-in-loop (HIL) test results also demonstrate the feasibility of the proposed controller. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
7. Compensating Delays and Noises in Motion Control of Autonomous Electric Vehicles by Using Deep Learning and Unscented Kalman Predictor.
- Author
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Li, Yanjun, Yin, Guodong, Zhuang, Weichao, Zhang, Ning, Wang, Jinxiang, and Geng, Keke
- Subjects
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DEEP learning , *NOISE control , *AUTONOMOUS vehicles , *ELECTRIC vehicles , *RECURRENT neural networks , *DRIVERLESS cars - Abstract
Accurate knowledge of the vehicle states is the foundation of vehicle motion control. However, in real implementations, sensory signals are always corrupted by delays and noises. Network induced time-varying delays and measurement noises can be a hazard in the active safety of over-actuated electric vehicles (EVs). In this paper, a brain-inspired proprioceptive system based on state-of-the-art deep learning and data fusion technique is proposed to solve this problem in autonomous four-wheel actuated EVs. A deep recurrent neural network (RNN) is trained by the noisy and delayed measurement signals to make accurate predictions of the vehicle motion states. Then unscented Kalman predictor, which is the adaption of unscented Kalman filter in time-varying-delay situations, combines the predictions of the RNN and corrupted sensory signals to provide better perceptions of the locomotion. Simulations with a high-fidelity, CarSim, full-vehicle model are carried out to show the effectiveness of our RNN framework and the entire proprioceptive system. [ABSTRACT FROM AUTHOR]
- Published
- 2020
- Full Text
- View/download PDF
8. A stair-like generalized predictive control based on multiple models switching for four-wheel-drive electric vehicle
- Author
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Zhang Ning, Xu Liwei, Jin Xianjian, Yin Guodong, and Fan Hui
- Subjects
0301 basic medicine ,0209 industrial biotechnology ,Engineering ,business.product_category ,Adaptive control ,business.industry ,Control engineering ,02 engineering and technology ,Optimal control ,Vehicle dynamics ,03 medical and health sciences ,Nonlinear system ,Model predictive control ,030104 developmental biology ,020901 industrial engineering & automation ,Control theory ,Electric vehicle ,Transient (oscillation) ,Four-wheel drive ,business - Abstract
A stair-like generalized predictive control (GPC)strategy based on multiple models switching for a 4-wheel-drive with 4 hub motors is presented in this paper. It ensures that the vehicle can change its motion softly and meet real-time optimal control requirements of systems with jumping parameters. The strong nonlinear dynamics and interaction characteristics of electric vehicle result in large model uncertainties and the conventional robust or parameter adaptive control methods can hardly ensure the stability and accuracy of vehicle motion without delay. A conventional adaptive vehicle model, an assigned initial value vehicle model and multiple fixed models are established to identify the vehicle dynamic characteristic in parallel. Multiple fixed vehicle models can improve the transient performance. Moreover, we ensure the stability of vehicle systems by the conventional adaptive vehicle and further enhance vehicle transient performance by the assigned initial value adaptive vehicle model. The best sub-model is selected as global model according to the switching index, and a stair-like generalized predictive controller is designed for this model in electric vehicle. Due to the GPC method employed in the design, the computation complexity and cost are greatly reduced. As a result, the vehicle delivers superior performance in hazardous driving conditions.
- Published
- 2017
9. Coordination control for formation and lateral stability under constant speed of four-wheel independently driving electric vehicles
- Author
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Yin Guodong, Zhang Ning, and Wang Ruifeng
- Subjects
0209 industrial biotechnology ,Engineering ,Lateral stability ,business.industry ,Control (management) ,Yaw ,Process (computing) ,02 engineering and technology ,Kinematics ,Vehicle dynamics ,020901 industrial engineering & automation ,Control theory ,0202 electrical engineering, electronic engineering, information engineering ,Torque ,020201 artificial intelligence & image processing ,business - Abstract
This paper presents a hierarchical control strategy for formation control of multiple four-wheel independently driving electric vehicles (4WIDEVs) under constant speed. The upper layer controller establishes formation mathematical model based on dynamic virtually leader-follower (DV-LF) method which transforms research for formation control into vehicle-following control and fuzzy PID algorithm is designed as vehicle following control strategy under constant speed. Considering the lateral stability of the following vehicle, the lower layer controller adopts torque distribution control strategy and the additional yaw moment controller is designed based on the static gain from the sideslip angle and yaw rate of the vehicle to improve the lateral stability in the process of forming the desired formation. In the end, in order to evaluate the performance of the proposed hierarchical control algorithm, the lane-change formation test condition under high constant speed is simulated in this paper and the simulation result shows that the coordination control strategy can achieve the desired formation control and improve the lateral stability of the following vehicle under high constant speed.
- Published
- 2017
10. Safety driving speed and lane keeping control for electric vehicle in variable curvature curve
- Author
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Yin Guodong, Cao Zhe, and Chen Jian-song
- Subjects
0209 industrial biotechnology ,Electronic speed control ,Engineering ,business.product_category ,business.industry ,020302 automobile design & engineering ,02 engineering and technology ,Function (mathematics) ,Curvature ,Vehicle dynamics ,Variable (computer science) ,Model predictive control ,020901 industrial engineering & automation ,0203 mechanical engineering ,Control theory ,Electric vehicle ,MATLAB ,business ,computer ,Simulation ,computer.programming_language - Abstract
This paper aims to analyze the safety of overactuated electric vehicle through variable curvature curve. By combined with previous general curve accident statistics, three kinds speed control targets can be presented, which is anti-skid, anti-roll and a longitudinal safety distance, to complete vehicle longitudinal dynamics control. Last, combining with the lane keeping system, fitting expectation path by the 5-spline function and using the model predictive control system, which vehicle front-wheel's angle can be achieved real-time correction, to complete vehicle lateral dynamics control. Through a combination of different curvatures curve, control simulation is conducted on vehicle dynamics model, and the feasibility of proposed methods is finally evaluated in Matlab/Simulink and CarSims. Besides, this paper will provide useful data as an accumulation of dynamic response a basis of further refinements in torque distribution control.
- Published
- 2017
11. Modeling and Robust Control of Heterogeneous Vehicle Platoons on Curved Roads Subject to Disturbances and Delays.
- Author
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Xu, Liwei, Zhuang, Weichao, Yin, Guodong, Bian, Chentong, and Wu, Huawei
- Subjects
ROBUST control ,DRAG (Aerodynamics) ,WIRELESS communications ,VEHICLE models ,STRUCTURAL dynamics - Abstract
This paper presents an integrated platoon control framework for heterogeneous vehicles on curved roads with varying slopes, aerodynamic drag, and wireless communication delays. First, a linear heterogeneous vehicle platoon model with decoupled longitudinal and lateral dynamics is built based on nonlinear feedback linearization and arc-length parametric transformation of an arbitrary curved road. The external disturbances are also considered, including the up-down road slopes, wind and equivalent time-delays caused by the wireless communication delay and discrete data in onboard sensors. Second, to achieve stable platoon control on a curved road, the platoon uses the state-feedback control method in the longitudinal direction while each vehicle tracks the centerline of the curved road to realize lateral control. Longitudinally, an $ H_\infty$ platoon controller is designed based on the Lyapunov-Krasovskii functional to ensure the inner-vehicle and string stability of the platoon, which suffers from parameter uncertainty, and external disturbances. Additionally, the $ \mathcal {L}_2$ string stability is defined to guarantee that the perturbations do not grow unbounded as they propagate through the platoon. Simulation results indicate that the proposed robust controller achieves proper platoon intervehicle spacing in both the longitudinal and lateral directions. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
12. Improving Vehicle Handling Stability Based on Combined AFS and DYC System via Robust Takagi-Sugeno Fuzzy Control.
- Author
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Jin, Xianjian, Yu, Zitian, Yin, Guodong, and Wang, Junmin
- Abstract
This paper presents a robust fuzzy $H_{\infty }$ control strategy for improving vehicle lateral stability and handling performance through integration of direct yaw moment control system (DYC) and active front steering. Since vehicle lateral dynamics possesses inherent nonlinearities, the main objective is dedicated to deal with the nonlinear challenge in vehicle lateral dynamics by applying Takagi-Sugeno (T-S) fuzzy modeling approach. First, the nonlinear Brush tire dynamics and the nonlinear functions of longitudinal velocity are represented via a T-S fuzzy modeling technique, and vehicle parametric uncertainties are handled by the norm-bounded uncertainties. An uncertain nonlinear vehicle lateral dynamic T-S fuzzy model is then obtained with multi-fuzzy-rules. The resulting robust fuzzy $H_{\infty }$ state-feedback controller is designed with the parallel-distributed compensation strategy and premise variables, and solved via a set of linear matrix inequalities derived from Lyapunov asymptotic stability and quadratic $H_{\infty }$ performance. Simulations for two different maneuvers are implemented with a high-fidelity, CarSimⓇ, full-vehicle model to verify the effectiveness of the developed approach. It is confirmed from the results that the proposed controller can effectively preserve vehicle lateral stability and enhance yaw handling performance. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
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