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Design of quasi fuzzy sliding mode based maneuvering of autonomous vehicle

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Abstract

Maneuvering of autonomous vehicles primarily relies on trajectory tracking control techniques to self-drive at predefined steering angle with parametric uncertainty and external perturbation. The steering mechanism in autonomous navigation must be reliable and extremely effective, even in challenging circumstances for nonlinear trajectory tracking and lane changing of autonomous vehicles. From a control point of view, fuzzy quasi-sliding mode control methodology was adopted to attenuate the effect of model parametric uncertainties, tire cornering stiffness, road bonding coefficient, measurement noises, longitudinal velocity and exogenous disturbances. The robust tracking control incorporates quasi-sliding mode control that ensures the lateral motion and yaw dynamics with nominal operating parameters by compensating nonlinear dynamics with model uncertainty and fuzzy logic approach accomplishes balance between chattering alleviation and tracking accuracy. The control algorithm is model-free and requires no prior knowledge of the bounds of uncertainties in the vehicle’s dynamic parameters. Lyapunov theory is used to prove the closed loop tracking control scheme global asymptotic stability. Finally, the efficiency and reliability of the suggested control strategy is confirmed through simulation based on three test scenarios and experimental validation conducted on dSPACE SCALEXIO hardware-in-loop platform for nonlinear trajectory tracking with input constraints.

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The authors declare no additional data and materials are submitted.

Abbreviations

m :

Vehicle mass (in kg)

I z :

Moment of inertia (in kg/m2)

L f :

Distance from front axle to center of the mass (in m)

L r :

Distance from rear axle to center of the mass (in m)

C f :

Front tire cornering stiffness (in kN/rad)

C r :

Rear tire cornering stiffness (in kN/rad)

V :

Velocity (in m/s)

V x :

Velocity along X axis (in m/s)

V y :

Velocity along Y axis (in m/s)

ψ :

Yaw angle (in °)

β :

Slip angle at center (in °)

θ :

Heading angle (in °)

δ :

Front wheel steering angle (in °)

α f :

Slip angle of front tyer (in °)

α r :

Slip angle of the rear tyer (in °)

R :

Tire radius (in m)

T w :

Braking wheel torque (in N m)

T b :

Brake torque (in N m)

F yf :

Front tire lateral force (in N)

F yr :

Rear tire lateral force (in N)

u :

Command control torque (in N m)

s :

Sliding manifold

V :

Lyapunov function

A f :

Longitudinal drag area (in m2)

C d :

Longitudinal drag coefficient

C l :

Longitudinal lift coefficient

C pm :

Longitudinal drag pitch moment

μ :

Nominal friction scaling factor

P abs :

Absolute pressure (in Pa)

g :

Gravitational acceleration (in m2)

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Acknowledgements

The work is supported by the Center of Intelligent Mobility (CIM), KLE Technological University, Hubli, Karnataka and collaborated with Department of Instrumentation and Control, COEP Technological University, Pune, Maharashtra. The authors would like to express their sincere gratitude to the Editor-in-Chief and anonymous reviewers whose constructive comments have helped us to significantly improve both the technical quality and presentation of this manuscript. Authors are deeply grateful to Head, Department of Instrumentation and Control engineering, COEP Technological University, Pune, M.S., for utilization of laboratory to carrying out research work.

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Authors and Affiliations

  1. School of Electronics and Communication, KLE Technological University, Hubli, Karnataka, India

    Raghavendra M. Shet & Nalini C. Iyer

  2. Department of Instrumentation and Control Engineering, COEP Technological University, Pune, Maharashtra, India

    Girish V. Lakhekar

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Contributions

Conceptualization, RMS, GVL; Methodology, RMS, GVL; Software, RMS, GVL; validation, RMS, GVL; Formal analysis, GVL, NCI; Investigation, RMS and GVL.; Resources, NCI.; Data curation, RMS and GVL; Writing—original draft preparation, RMS and GVL; Writing—review and editing, RMS, GVL and NCI.; Visualization, RMS and GVL.; Supervision, NCI; Project administration, NCI; Funding acquisition, NCI. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Raghavendra M. Shet.

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Shet, R.M., Lakhekar, G.V. & Iyer, N.C. Design of quasi fuzzy sliding mode based maneuvering of autonomous vehicle. Int. J. Dynam. Control 12, 1963–1986 (2024). https://doi.org/10.1007/s40435-023-01308-0

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