Title: Vehicle longitudinal force estimation using adaptive neural network nonlinear observer

Authors: Mourad Boufadene; Mohammed Belkheiri; Abdelhamid Rabhi; Ahmed El Hajjaji

Addresses: Laboratory of Telecommunications, Signals and Systems, University Amar Telidji of Laghouat, PB. 37G Ghradaia Road, 03000, Laghouat, Algeria ' Laboratory of Telecommunications, Signals and Systems, University Amar Telidji of Laghouat, PB. 37G Ghradaia Road, 03000, Laghouat, Algeria ' Laboratory of Modeling, Information and Systems, University of Picardie Jules Verne, 33 rue Saint Leu – 80039 Amiens Cedex 1, France ' Laboratory of Modeling, Information and Systems, University of Picardie Jules Verne, 33 rue Saint Leu – 80039 Amiens Cedex 1, France

Abstract: This paper presents an adaptive neural network (NN) nonlinear observer to estimate the longitudinal tyre forces as well as the lateral speed which is not measured on standard vehicles. The proposed adaptive neural network (NN) observer uses the longitudinal speed, yaw rate and the steering angle dynamics of the vehicle as measured states. It is used to estimate the states, and the longitudinal tyre forces, which are unknown dynamics, with high performance. The obtained simulation results show the effectiveness of the proposed neural network nonlinear observer.

Keywords: adaptive observer; adaptive neural network; radial basis function approximation; nonlinear observer; vehicle force estimation; tyre forces estimation; longitudinal vehicle force estimation.

DOI: 10.1504/IJVD.2019.103593

International Journal of Vehicle Design, 2019 Vol.79 No.4, pp.205 - 220

Received: 23 Nov 2017
Accepted: 14 Sep 2018
Published online: 13 Nov 2019 *

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