Improving Handling Stability Performance of Four-Wheel Steering Vehicle via $\mu$-Synthesis Robust Control

Yin, Guodong; Chen, Nan; Li, Pu

doi:10.1109/tvt.2007.899941

Cited by 84 publications

(34 citation statements)

References 13 publications

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“…In this paper, a classical two-DOF bicycle model for 4WS vehicle handling dynamics is used for the desing of a controller. Figure 1 shows a half vehicle dynamic model related to driver steering manoeuvers, travelling on a road surface at a constant speed v with the tyre steering angle δ f and δ r A differential equation of the vehicle dynamics model is obtained [2,7].…”

Section: A Mathematical Modelmentioning

confidence: 99%

“…To deal with the system perturbations, the weighting function is a key issue in the μ-synthesis design procedure. Before starting, it is necessary to formalize the uncertainties and system specification in term of a suitable general framework which is 4WS vehicle closed-loop control system based on μ-synthesis ( Fig.1) [7].…”

Section: B Referencesdesign Of Controllermentioning

confidence: 99%

“…The vehicle yaw rate is chosen as the only feedback signal to avoid the practical difficulty for measuring the GC sideslip angle of the vehicle. The detailed process of robust controller design is in reference [7]. The numerical simulation show that the 4WS vehicle equipped with the μ-synthesis robust controller has better maneuverability and stronger ability to resist the disturbance; it is not sensitive to the variation of vehicle parameters.…”

Section: B Referencesdesign Of Controllermentioning

confidence: 99%

“…The μsynthesis uses a structured singular value μ to distinguish the detail of system perturbation. By considering the structure of the perturbation, the designed μ-synthesis controller for four-wheel steering vehicle can achieve preferable dynamic and steady-state performance [7]. Unfortunately, most studies have focused on the theoretical study of 4WS and there have been few experimental studies.…”

Section: Introductionmentioning

confidence: 99%

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μ-synthesis robust control for four-wheel steering vehicle with Hardware-in-the-Loop-Simulation system

Yin

Chen

2008

2008 IEEE Vehicle Power and Propulsion Conference

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A Hardware-in-the Loop Simulation (HILS) platform based on Matlab/Simulink/dSPACE is developed, which can realtimely adjust the control parameters and measure the different inputs and response, and can carry through the virtual testing by constructing different vehicle surrounding. The yaw-rate feedback is taken as the basic control logic for 4WS vehicle, which is easy to use. Large online real-time synthesis is required for developing the control system. The platform can also be used for different vehicle ECU developing. With the HILS platform the robustness and other performances for different control arithmetics are compared and the performance of the system is investigated by experiment, the results show that the μ-synthesis robust controller has better general performance.

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Section: A Mathematical Modelmentioning

confidence: 99%

Section: B Referencesdesign Of Controllermentioning

confidence: 99%

Section: B Referencesdesign Of Controllermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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μ-synthesis robust control for four-wheel steering vehicle with Hardware-in-the-Loop-Simulation system

Yin

Chen

2008

2008 IEEE Vehicle Power and Propulsion Conference

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“…Mainly due to increased mechanical complexity, these solutions are not spread in commercial light vehicles, however many studies have evaluated the advantages introduced by an active rear steering. In [6] and [7] decoupling control architectures have been proposed in order to reduce the interaction between the yaw rate and lateral dynamics, while in [8], [9], [10] and [11] those tire cornering stiffness is a key influencing factor on maneuverability. The present work is an extension of the previous one in [12] and [13] where a collaborative control of active front steer and rear brake torques is proposed.…”

Section: Introductionmentioning

confidence: 99%

Advantages of rear steer in LTI and LPV vehicle stability control

Selmanaj

Corno²,

Sename³

et al. 2013

52nd IEEE Conference on Decision and Control

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Abstract-In this paper, the advantages of the rear wheel steer in robust yaw stability control of four wheeled vehicles are shown. A MIMO vehicle dynamic stability controller (VDSC) involving front steer, rear steer and rear braking torques is synthesized. The comparison between a vehicle with and without rear steer is done on avoidance maneuver using both LTI and gain-scheduling LPV controller. Both robust H ∞ controllers are built by the solution of an LMI problem. To better evaluate the influence of the rear steer on the performance time domain indexes are introduced. The simulation results show that active rear steer enhances vehicle handling on a low friction surface.

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Integrated vehicle control using adaptive control allocation

Temiz

Çakmakçı

Yıldız

2023

Adaptive Control & Signal

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Summary The focus of this paper is an integrated, fault‐tolerant vehicle control algorithm for the overall stability of ground vehicles. The proposed scheme comprises a high‐level controller that creates a virtual control input and a low‐level adaptive control allocator that distributes the virtual control effort among redundant actuators. The proposed control framework distinguishes itself from earlier results in the literature by its ability to blend active suspension, steering and traction control channels, in the presence of uncertainties and time‐varying dynamics, without the need for fault identification. The control structure is validated in the simulation environment using a fourteen‐degree‐of‐freedom non‐linear vehicle model. The integrated controller is compared to the case of a conventional control approach where each control problem is solved separately. Our results show that, compared to the conventional approach, the proposed method ensures that the vehicle follows driver inputs with up to bold33$$ \mathbf{33} $$% higher longitudinal maneuver velocity, despite the presence of actuator failures and slippery road conditions. Furthermore, to demonstrate the benefit of integrating active suspension control to the overall control scheme, we replaced the suspension control of the proposed approach with an independent suspension control system for comparison purposes. We then showed that the integrated case provided bold24$$ \mathbf{24} $$% lower roll angle deviation, and bold20$$ \mathbf{20} $$% lower pitch angle deviation, in the presence of actuator effectiveness loss and adverse road conditions.

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Improving Handling Stability Performance of Four-Wheel Steering Vehicle via $\mu$-Synthesis Robust Control

Cited by 84 publications

References 13 publications

μ-synthesis robust control for four-wheel steering vehicle with Hardware-in-the-Loop-Simulation system

μ-synthesis robust control for four-wheel steering vehicle with Hardware-in-the-Loop-Simulation system

Advantages of rear steer in LTI and LPV vehicle stability control

Integrated vehicle control using adaptive control allocation

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Improving Handling Stability Performance of Four-Wheel Steering Vehicle via $\mu$-Synthesis Robust Control

Cited by 84 publications

References 13 publications

&#x03BC;-synthesis robust control for four-wheel steering vehicle with Hardware-in-the-Loop-Simulation system

&#x03BC;-synthesis robust control for four-wheel steering vehicle with Hardware-in-the-Loop-Simulation system

Advantages of rear steer in LTI and LPV vehicle stability control

Integrated vehicle control using adaptive control allocation

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μ-synthesis robust control for four-wheel steering vehicle with Hardware-in-the-Loop-Simulation system

μ-synthesis robust control for four-wheel steering vehicle with Hardware-in-the-Loop-Simulation system