Development of neural-network control of steer-by-wire system for intelligent vehicles

Most of the chassis systems are developed by automotive suppliers to improve a specific vehicle performance. Drivers, and consequently vehicle manufacturers, are more concerned by the overall behaviour of the Vehicle. Many coordination architectures have been proposed in the literature in order to integrate different chassis systems in a single vehicle. In this paper, these architectures are compared and discussed. Two major classes are proposed: Downstream and Upstream Coordination. The purpose of this classification is to help car manufacturers and suppliers standardize an Integrated Vehicle Dynamics Control architecture for faster and more flexible designs.

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“…These functions could be chosen to ensure smooth transitions between coordination modes, actuator saturation avoidance, etc. [12].…”

Section: Artificial Neural Networkmentioning

confidence: 99%

Review of integrated vehicle dynamics control architectures

Kissai

Monsuez

Tapus

2017

2017 European Conference on Mobile Robots (ECMR)

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“…Most of control techniques used in the previous studies fall into the first category. Examples include nonlinear predictive control [3], random sub-optimal control [4], robust H ∞ [5], sliding mode [6], and artificial neural networks [7], etc. In contrast, hierarchical control has not yet been applied extensively to integrated vehicle control system.…”

Section: Introductionmentioning

confidence: 99%

Integrated control of active suspension system and electronic stability programme using hierarchical control strategy: theory and experiment

Xiao

Chen

Zhou

et al. 2011

Vehicle System Dynamics

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Integrated vehicle dynamics control has been an important research topic in the area of vehicle dynamics and control over the past two decades. The aim of integrated vehicle control is to improve the overall vehicle performance including handling, stability, and comfort through creating synergies in the use of sensor information, hardware, and control strategies. This paper proposes a two-layer hierarchical control architecture for integrated control of the active suspension system (ASS) and the electronic stability programme (ESP). The upper-layer controller is designed to coordinate the interactions between the ASS and the ESP. While in the lower layer, the two controllers including the ASS and the ESP are developed independently to achieve their local control objectives. Both a simulation investigation and a hardware-in-the-loop experimental study are performed. Simulation results demonstrate that the proposed hierarchical control system is able to improve the multiple vehicle performance indices including both the ride comfort and the lateral stability, compared with the non-integrated control system. Moreover, the experimental results verify the effectiveness of the design of the hierarchical control system.

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“…Most control techniques used in the previous studies fall into the first category. Examples include nonlinear predictive control (Falcone et al, 2007), random sub-optimal control (Chen et al, 2006), robust H  (Hirano et al, 1993), sliding mode , and artificial neural networks (Nwagboso et al, 2002), etc. In contrast, hierarchical control has not yet been applied extensively to integrated vehicle control system.…”

Section: Introductionmentioning

confidence: 99%