Gain-scheduling robust control for a tire-blow-out road vehicle

Jing, Houhua; Liu, Zhiyuan

doi:10.1177/0954407017743411

Cited by 15 publications

(18 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [27], a predictive safety control method for the road vehicle after tire blowout was designed by introducing driving assistant system, which provided a lateral stability control framework for the vehicle with tire blowout. In [28], a gain-scheduling H ∞ control approach was proposed to enhance vehicle stability with respect to time-varying vehicle velocity as well as uncertain tire cornering, and the simulation results demonstrated the effectiveness of control approach. These studies greatly improve vehicle stability with tire blowout through the advanced control algorithm, such as predictive control, robust control, etc.…”

Section: Literature Reviewmentioning

confidence: 98%

RBFNN based terminal sliding mode adaptive control for electric ground vehicles after tire blowout on expressway

Yang

Yue

Liu

et al. 2020

Applied Soft Computing

View full text Add to dashboard Cite

This paper proposes a radial basis function neural network (RBFNN) based terminal sliding mode control scheme for electric ground vehicles subject to tire blowout on expressway in presence of tire nonlinearities, unmodeled dynamics and external disturbances. For enhancing the longitudinal and lateral stability of the vehicle after tire blowout, a saturated velocity planner is firstly constructed for tracking the original motion trajectory, by which the longitudinal velocity and yaw rate saturation constraints can be effectively handled. Afterwards, a terminal sliding mode controller (TSMC) is designed for tracking the planned velocity signals because of its inherent finite time convergence rate and superior steady-state property, by which the adverse dynamic behaviors can be timely suppressed. Further, to strengthen the adaptability and robustness of the control scheme, a RBFNN approximator is developed for identifying the lumped uncertainty, such as tire nonlinearities, unmodeled dynamics and external disturbances, etc., and then compensated into the controller. Lastly, simulations with front-right tire blowout on expressway are performed to validate the effectiveness and efficiency of presented control scheme and methods, and the comprehensive performance of TSMC+RBFNN and TSMC schemes in maintaining original trajectory tracking capacity is evaluated and discussed.

show abstract

Section: Literature Reviewmentioning

confidence: 98%

RBFNN based terminal sliding mode adaptive control for electric ground vehicles after tire blowout on expressway

Yang

Yue

Liu

et al. 2020

Applied Soft Computing

View full text Add to dashboard Cite

show abstract

“…The generated biased torque produces a controlled yawing moment that counteracts and balances out the blowout-induced yaw disturbance. Such an apparatus does not require the installation of any extra actuators because the braking/traction torque distribution is already implemented in the ESC system which by itself is incapable to stabilize the vehicle under such a severe transient [11]. The blown tire side is excluded from the application of input torques to prevent the relative movement between the hub and the tire as well as to avoid wheel locking.…”

Section: Controller Designmentioning

confidence: 99%

“…Differential braking systems utilize biased distributive braking or traction torques to induce the regulated yaw moment needed to stabilize the vehicle. This principle along with different control apparatuses and optimization techniques have been analyzed comprehensively to mitigate the consequences of the tire blowout problem [11]. However, none of these studies accounted for the possible random interventions from the human driver.…”

Section: Introductionmentioning

confidence: 99%

A Nonlinear Tire Blowout Stabilizer Based on a Novel Integral Terminal Sliding Mode Controller

Al-Quran

Mayyas

2021

IEEE Access

View full text Add to dashboard Cite

This paper proposes an automatic corrective safety controller design and evaluation based on braking/traction actuation to enhance the stability of a ground vehicle subjected to a tire blowout. Along with the nonlinear Dugoff's tire model, a nonlinear planar seven degrees of freedom control-oriented vehicle model is developed and validated using MSC Adams/ car package. The proposed novel controloriented model accounts for the longitudinal dynamics, large steering and slip angles, and the nonlinearities associated with the vehicle/tire coupled system. In consequence, a distributive torque control technique in the framework of the integral terminal sliding mode controller is established. The integral action is employed in the sliding surfaces to enhance the steady-state tracking performance of the closed-loop system. The controller distributes the control torque demand among the three inflated tires excluding the blown tire to counteract the blowout-induced yawing disturbance. Two control strategies are introduced to facilitate controller practical implementation in both electric and conventional vehicles. The results indicate that the proposed controller is perfectly competent to stabilize the vehicle and robustly track the desired trajectory in a straight line and curvilinear motions as well as under nonlinear operating conditions. INDEX TERMS Tire blowout, vehicle dynamics, stability control, ITSMC.

show abstract

“…For the lateral controller design, it is not preferred to employ the complicated vehicle dynamics model for constructing the stability controller due to the requirements of rapid reaction subject to tire blowout (Jing and Liu, 2019). Ignoring vertical, pitch and roll motions, the vehicle lateral dynamic control model in yaw-plane can be expressed as…”

Section: Control System Synthesizementioning

confidence: 99%

Tire blow-out control for direct drive electric vehicles using reconfiguration of torque distribution and vertical load

Yang

Yue

Tian

et al. 2020

Transactions of the Institute of Measurement and Control

View full text Add to dashboard Cite

This paper proposes a composite stability control strategy for tire blowout electric vehicle with explicit consideration of vertical load redistribution, subject to multi-constraints, uncertainty and redundant actuation. To readily implement system state and actuator increment constraints, a model predictive controller is designed to enhance vehicle stability performance and original lane keeping. Meanwhile, a sliding mode control-based longitudinal velocity controller is collaboratively proposed for maintaining the original longitudinal velocity after tire blowout in the freeway, which can reduce considerably the rear-end collision accidents. After that, a constrained weighting least square-based reconfigurable torque distributor is developed to realize the tracking of the virtual resultant yaw-moment and longitudinal tire force signals generated by the above controllers, considering system physical constraints and actuator capability simultaneously. Simulations with different tire blowout scenarios are conducted on the developed dynamic simulation platform to demonstrate the effectiveness of the designed control methods; furthermore, the influence of different tire blowout on the vehicle movement behaviors is discussed. Statistical results based on the system transient performance and control effort evaluating indictors highlight the considerable superiority of the developed model predictive controller compared with the linear quadratic regulator.

show abstract

Gain-scheduling robust control for a tire-blow-out road vehicle

Cited by 15 publications

References 30 publications

RBFNN based terminal sliding mode adaptive control for electric ground vehicles after tire blowout on expressway

RBFNN based terminal sliding mode adaptive control for electric ground vehicles after tire blowout on expressway

A Nonlinear Tire Blowout Stabilizer Based on a Novel Integral Terminal Sliding Mode Controller

Tire blow-out control for direct drive electric vehicles using reconfiguration of torque distribution and vertical load

Contact Info

Product

Resources

About