Regional path moving horizon tracking controller design for autonomous ground vehicles

Guo, Hongyan; Liu, Feng; Yu, Ru; Sun, Zhenping; Chen, Hong

doi:10.1007/s11432-016-0310-1

Cited by 19 publications

(10 citation statements)

References 5 publications

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“…Discretization of RINS continuous-time model. Before Kalman filter is applied to RINS/GNSS integrated navigation system, the continuous-time models of RINS equations (27) and (28) and GNSS equation (29) need to be discretized respectively. The discretized error dynamic equation of equation (27) is…”

Section: Discretization Of Continuous-time Modelmentioning

confidence: 99%

An improved integrated navigation method based on RINS, GNSS and kinematics for port heavy-duty AGV

Feng

Duan³

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part D:

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The current navigation methods for port heavy-duty automated guided vehicle mainly include the antenna radar-transponder navigation and the global navigation satellite system. However, the former has a huge cost and the latter will generate multi-path error easily. To avoid these problems, an improved integrated navigation method based on single-axis rotating inertial navigation system, global navigation satellite system and kinematics is proposed. First, the rotating inertial navigation system/ global navigation satellite system and rotating inertial navigation system/Kinematics integrated navigation methods generate corresponding estimates and filtering error covariances through their respective extended Kalman filter filters, and then the two sets of results are fused by the optimal weighted voting fusion method. The proposed method is applied to a heavy-duty automated guided vehicle for engineering verification. Without multi-path error, the navigation accuracy is 1.8–2.98 times higher than that of the traditional global navigation satellite system navigation. In the case of multi-path error, the improved method still has high fault tolerance and high navigation accuracy. The accuracy of this method satisfies the requirements of port heavy-duty automated guided vehicle, which can greatly reduce the number of transponders and has high practical value.

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Section: Discretization Of Continuous-time Modelmentioning

confidence: 99%

An improved integrated navigation method based on RINS, GNSS and kinematics for port heavy-duty AGV

Feng

Duan³

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part D:

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“…where T mj,max and P mj,max are respectively the maximum braking torque and power of the in-wheel motor. In order to find the real-time solution of the formulated optimization problem, the model predictive control method is used to design the controller, which is one of the most effective methods to deal with a control problem with multiple constraints [19], [20]. The basic theory of MPC can be described as, at every sampling moment, according to the current measurement state information to obtain the solution of a finite time optimization problem.…”

Section: A Mpc Based Velocity-tracking Controllermentioning

confidence: 99%

Velocity Optimization for Braking Energy Management of In-Wheel Motor Electric Vehicles

Chen

Wang

et al. 2019

IEEE Access

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This paper presents two braking regenerative energy optimization controllers for in-wheel motor electric vehicles. The first one is a velocity-tracking controller based on a model predictive control (MPC) method to recover the braking energy. It takes the front and rears in-wheel motor efficiencies into account to distribute the hydraulic and in-wheel motor braking torque of the front and rear wheels. As the vehicle information and intelligence have brought new opportunities for energy management, another velocity optimization controller is designed by considering the restricted condition of terminal distance and terminal velocity. In this strategy, a receding-horizon MPC method is proposed to solve the restricted nonlinear optimal problem. Furthermore, this optimization algorithm is transformed from the time horizon to the distance horizon to satisfy the terminal distance constraint. AMESim/Simulink co-simulations are carried out to evaluate the effectiveness of the proposed controllers. The simulation results indicate that the velocity optimization method can achieve the braking requirement as well as effectively promote regenerative efficiency. INDEX TERMS Electric vehicle, regenerative braking, energy management, model predict control.

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“…For instance, an adaptive cruise-control system involves little lateral control of the vehicle [23], and a lane-changing controller cannot be directly applied to emergency collision avoidance or intersection problems, although lateral control has been involved [12]. Model predictive control (MPC) can be a superior method for the online solution of the optimal trajectory [24], [25]. In MPC methods, the optimal problem can be online solved in a moving predictive horizon [26], [27], which provides great advantages in changing the predictive model, predictive horizon, constraints, performance index, and even the optimal problem form.…”

Section: A State-of-the-art Review and Challengesmentioning

confidence: 99%

A Novel Trajectory Planning Method for Automated Vehicles Under Parameter Decision Framework

et al. 2019

Self Cite

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Decision and control in all stack scenarios comprise a key issue in the design of automated vehicle control systems. Thus, in higher level, automated vehicles, the decision and the form of the decision should be able to adapt to diverse, changeable, and complex scenarios, which increase the complexity of trajectory planning. In this paper, a parameter decision framework in which the decision is described with key parameters, rather than specific behaviors, such as lane-changing or car-following, is considered. Under this framework, a novel trajectory planning method is proposed to implement behavior with integrated longitudinal and lateral control, in which a nonlinear motion control model is established. The nonlinear model predictive control (NMPC) method with terminal constraints without a predefined path form is applied, which presents more flexibility for changeable decisions. Both the trajectory planning controller and the overall framework are verified by simulation. The results show the validity of the controller and the framework. INDEX TERMS Model predictive control, trajectory planning, decision-making, integrated longitudinal and lateral control.

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Regional path moving horizon tracking controller design for autonomous ground vehicles

Cited by 19 publications

References 5 publications

An improved integrated navigation method based on RINS, GNSS and kinematics for port heavy-duty AGV

An improved integrated navigation method based on RINS, GNSS and kinematics for port heavy-duty AGV

Velocity Optimization for Braking Energy Management of In-Wheel Motor Electric Vehicles

A Novel Trajectory Planning Method for Automated Vehicles Under Parameter Decision Framework

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