Research paperSimultaneous path following and lateral stability control of 4WD-4WS autonomous electric vehicles with actuator saturation
Introduction
In recent years, with the deepening of automotive technology research, intelligent automobile technology has developed rapidly and received unprecedented attention from the researchers in the automotive industry and even related intersecting fields like computer technology and artificial intelligence technology [1], [2], [3], [4], in which the autonomous vehicle driving technology with L3 level is the focus of current industry research [5], [6]. Path following control of unmanned vehicle is one of the most important research problems in the development process of vehicle intelligentization and many fruitful research results have been achieved at present [7], [8], [9]. Guo et al. [10] studied the dual-envelop-oriented moving horizon path following control problem considering the influence of vehicle size to the feasible area in path tracking process, in which the model predictive control algorithm is used to improve the time-varying ability and tracking accuracy of the path following controller. Leng and Minor [11] presented a path following control method of trailer by combining the feedforward control with feedback control strategy with the problem of steering saturation being considered at the same time.
In the existing research literatures, the control algorithms like model predictive control [12], robust control [13], [14], [15], sliding mode control [16], [17], [18] and combined control method of the above algorithms are widely used to design the path following controller of autonomous ground vehicles. Kim et al. [12] applied the dynamic characteristics of vehicle steering system to the path following controller design and improved vehicle path tracking performance on the basis of model predictive control algorithm. Behrooz et al. [15] proposed a robust controller design method for vehicle path following control based on μ-synthesis method on the premise of considering the uncertainty of vehicle model.
By analyzing and summarizing the previous research achievements, one can find that researchers usually consider the influences of some saturation or disturbance conditions such as parameter perturbation of vehicle system model or time lag [13], uncertain disturbance [19] and actuator saturation [20], and they pay more attention to solve the reliability and adaptability of path following control system under multiple factors, so as to improve vehicle tracking accuracy and real-time adjustment ability [21], [22]. Wang et al. [13], [20], [23] studied the applications of some control theories like robust H∞ control and sliding mode control and verified the vehicle performance in the process of vehicle path following in which some factors like time delay, data dropout and model uncertainty are taken into consideration.
With the further development and prolongation of research, some literatures tend to discuss and study the integrated control method of vehicle stability and path following considering the coupling relationship of multiple actuators [24], [25], [26]. Zhang et al. [26] presented an adaptive cruise system to ensure vehicle path following control ability while realizing the direct yaw moment control of autonomous vehicle. Ni et al. [27], [28] designed an integrated control strategy for path following control and vehicle stability control and applied it on a four-wheel independent drive autonomous electric vehicle, in which the algorithm for vehicle longitudinal, lateral and yaw dynamics control is designed and the control demand is achieved through steering control and optimal tire force distribution.
In recent years, the four-wheel independent drive electric vehicles have attracted the attention of academic communities and been widely and deeply studied due to the controllability with high degree of freedom and the accurate and independent torque allocation [29], [30], [31], [32], [33]. Furthermore, the four-wheel independent drive and four-wheel independent steering (4WD-4WS) vehicle has higher control freedom than traditional cars [34], [35], [36], if we can study the path following control problem on this vehicle platform, it will emerge great potential to improve the performance of vehicle path following and stability control at the same time.
In this paper, a novel hierarchical vehicle control strategy was presented for simultaneous path following and lateral stability control of 4WD-4WS autonomous electric vehicles considering the actuator saturation based on Hamilton energy function. A global hierarchical control method was proposed, in which the upper layer controller was designed on the basis of combined vehicle dynamics model and path following model and applied to achieve the simultaneous path following and lateral stability control of vehicle, and the convergence of proposed controller was proved. The lower layer controller was designed to satisfy the control command of upper layer controller by orientated tire force allocation in real time.
The rest of this paper is organized as follows. The vehicle model is presented is Section 2. The integrated control method of vehicle path following and lateral stability is designed in Section 3. The simulation results are provided in Section 4, followed by the conclusive remarks in Section 5.
Section snippets
Vehicle dynamics model
In this section, a two-degree-of-freedom vehicle model in lateral and yaw directions is introduced to characterize the vehicle motion, the schematic diagram of the vehicle dynamics model is shown in Fig. 1. The origin of dynamic coordinate system xoy is fixed on the vehicle coincides with the vehicle gravity center, the x axis is the longitudinal axis of the vehicle (the forward direction is positive), the y axis is the lateral axis of the vehicle (the right-to-left direction is positive). The
Global control strategy
The integrated path following and lateral stability control of vehicle is discussed in Section 3, and the global vehicle control strategy is shown in Fig. 3. The hierarchical control strategy is widely used and effective in controller design of in-wheel motor drive electric vehicles. As shown in Fig. 3, the errors between desired vehicle states and real vehicle states, and the lateral offset and heading error are used as the inputs of the upper layer controller. The upper layer controller is
Simulation results
In this section, to validate the effectiveness of designed integrated control strategy in this work, two simulation cases including the constant radius circular path maneuver and the lane change maneuver are carried out in a high-fidelity CarSim-Simulink co-simulation platform. The CarSim is used to provide the whole vehicle model, and the proposed control strategy is implemented on Matlab/Simulink. The parameters of vehicle and in-wheel motors are listed in Table 1. The vehicle speed is set as
Conclusion
To achieve the path following control of 4WD-4WS autonomous electric vehicles while ensuring the stability of vehicle at the same time, an integrated control strategy with hierarchical control structure was presented in this paper. Both two-degree-of-freedom vehicle model and path following model are developed. The hierarchical vehicle control strategy was proposed, and in the design process of upper layer controller, the Hamilton energy function control theory was used to design the vehicle
Conflict of interests
The authors declare that there is no conflict of interests regarding the publication of this paper.
Acknowledgments
The authors are grateful for the support provided by the National Natural Science Foundation of China (grant numbers U1564201 and U1664258), 333 Project of Jiangsu Province (grant number BRA2016445), Key R&D Plan of Jiangsu Province (grant number BE 2017129), and Natural Science Foundation of Jiangsu Province (grant number BK 20160525).
References (37)
- et al.
Precise trajectory optimization for articulated wheeled vehicles in cluttered environments
Adv Eng Softw
(2016) - et al.
Shared control for lane departure prevention based on the safe envelope of steering wheel angle
Control Eng Pract
(2017) - et al.
Dual-envelop-oriented moving horizon path tracking control for fully automated vehicles
Mechatronics
(2018) - et al.
Terminal sliding mode control of automated car-following system without reliance on longitudinal acceleration information
Mechatronics
(2015) - et al.
Integrated adaptive dynamic surface car-following control for nonholonomic autonomous electric vehicles
Sci China Technol Sci
(2017) - et al.
Robust H∞; output-feedback control for path following of autonomous ground vehicles
Mech Syst Signal Process
(2016) - et al.
Robust H∞; output-feedback yaw control for in-wheel motor driven electric vehicles with differential steering
Neurocomputing
(2016) - et al.
Dynamics control of autonomous vehicle at driving limits and experiment on an autonomous formula racing car
Mech Syst Signal Process
(2017) - et al.
Robust lateral motion control of four-wheel independently actuated electric vehicles with tire force saturation consideration
J Franklin Inst
(2015) - et al.
Estimation of longitudinal force, lateral vehicle speed and yaw rate for four-wheel independent driven electric vehicles
Mech Syst Signal Process
(2018)
Integrated optimal dynamics control of 4WD4WS electric ground vehicle with tire-road frictional coefficient estimation
Mech. Syst. Signal Process
L2-gain and passivity techniques in nonlinear control
Automatica
Saliency-based pedestrian detection in far infrared images
IEEE Access
On the use of Monte-Carlo simulation and deep fourier neural network in lane departure warning
IEEE Intell Transp Syst Mag
Path tracking control of automatic parking for intelligent vehicle based on non-smooth control strategy
J Jiangsu Univ
Path tracking control of automatic parking cloud model considering the influence of time delay
Math Probl Eng
Multilevel framework to handle object occlusions for real-time tracking
IET Image Proc
Visual vehicle tracking based on deep representation and semisupervised learning
J Sensors
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