A Computationally Efficient Path Following Control Strategy of Autonomous Electric Vehicles with Yaw Motion Stabilization

GUO, Ningyuan, ZHANG, Xudong, ZOU, Yuan, LENZO, Basilio and ZHANG, Tao (2020). A Computationally Efficient Path Following Control Strategy of Autonomous Electric Vehicles with Yaw Motion Stabilization. IEEE Transactions on Transportation Electrification, p. 1.

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Official URL: https://ieeexplore.ieee.org/document/9091169
Link to published version:: https://doi.org/10.1109/tte.2020.2993862


his paper proposes a computationally efficient path following control strategy of autonomous electric vehicles (AEVs) with yaw motion stabilization. First, the nonlinear control-oriented model including path following model, single track vehicle model, and Magic Formula tire model, are constructed. To handle the stability constraints with ease, the nonlinear model predictive control (NMPC) technique is applied for path following issue. Here NMPC control problem is reasonably established with the constraints of vehicle sideslip angle, yaw rate, steering angle, lateral position error, and Lyapunov stability. To mitigate the online calculation burden, the continuation/ generalized minimal residual (C/GMRES) algorithm is adopted. The deadzone penalty functions are employed for handling the inequality constraints and holding the smoothness of solution. Moreover, the varying predictive duration is utilized in this paper so as to fast gain the good initial solution by numerical algorithm. Finally, the simulation validations are carried out, which yields that the proposed strategy can achieve desirable path following and vehicle stability efficacy, while greatly reducing the computational burden compared with the NMPC controllers by active set algorithm or interior point algorithm.

Item Type: Article
Additional Information: © 2020 IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords: 0906 Electrical and Electronic Engineering
Identification Number: https://doi.org/10.1109/tte.2020.2993862
Page Range: p. 1
SWORD Depositor: Symplectic Elements
Depositing User: Symplectic Elements
Date Deposited: 27 May 2020 16:35
Last Modified: 18 Mar 2021 01:18
URI: https://shura.shu.ac.uk/id/eprint/26374

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