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Low rate error modeling of articulated heavy vehicle dynamics and experimental validation

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  • Control Theory and Applications
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Abstract

In the automotive domain, adequate control and diagnosis rely on the use of state observers and parametric identification systems to estimate the dynamics performances of the vehicle. Unfortunately, the simultaneous use of different methods of observation, estimation and identification is not risk-free. The risks can be expressed mathematically through a problem of error accumulation, posing major risks for the vehicle and its driver (errors of detection, errors in the prediction of dangerous driving situations, vehicle instability, etc.). This paper presents a method of observation and estimation of the dynamic state and parameter identification of an articulated vehicle simultaneously at very low error rates. This method is based on the HOSM (High Order Sliding Modes) approach, with the application of the STA (Super-Twisting Algorithm). Towards to this aim, a 5-DOF (Degree Of Freedom) nonlinear dynamic model for an articulated vehicle is proposed. The model is derived by applying Lagrange’s equations. Simulation and experimental results showed that the algorithms generate accurate estimation of articulated vehicle parameters and states dynamics in real driving situations.

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Author information

Authors and Affiliations

  1. Skid Resistance and Heavy Vehicle Safety in CEREMA, 25, Av François Mitterrand, 69500, Bron, France

    Mohamed Bouteldja

  2. EASE at IFSTTAR, AME-EASE, Route de Bouaye, CS4, 44340, Bouguenais, France

    Veronique Cerezo

Authors
  1. Mohamed Bouteldja
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  2. Veronique Cerezo
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Corresponding author

Correspondence to Mohamed Bouteldja.

Additional information

Recommended by Associate Editor Shihua Li under the direction of Editor Hyun-Seok Yang. The authors would like to acknowledge, Mr P-J Le Bec, engineer at the UTAC (service “Comportement Sécurité Active dynamique du véhicule”), France, for providing field test data.

Mohamed Bouteldja is Researcher in CEREMA (French Ministry of Transport), at laboratory of Lyon, France since 2008. He graduated with a Mechanical Engineering degree from the University of Blida in Algeria in 2000, then he obtained a Master’s degree in Robotics in 2002 and PhD degree in Automatics&Robotics in 2005 from Versailles Saint Quentin-en-Yvelines University (France). Between 2005 and 2008, he was researcher at LCPC on automatic weigh-in-motion of the trucks and road safety to identify road risk areas and vehicle risk situations. His main research interest includes heavy vehicle dynamic modelling and design, road and bridge damage, warning strategy and accident risk prediction, and driving assistance. He also has interests in non-linear continuous time-dependent systems, sliding mode control and observers, fault detection, and vehicle and power systems. Since mid-2012, head of research team «skid resistance and safety»at the Laboratory Department of Lyon (JRU of IFSTTAR). He was involved in several French and European research projects dealing with road safety such as TRANSFORMERS on the future heavy vehicles stability.

Veronique Cerezo is a civil engineer graduated from the National School of Public Works (ENTPE) of Lyon (France). She passed a PhD, in civil engineering and construction in Lyon. She spent nine years at Cerema in Lyon first as researcher than as head of the research team ‘skid resistance, safety and heavy vehicles’. In 2012, she joined the Research Laboratory EASE (Environmental Assessment, Safety and Ecodesign) at IFSTTAR in Nantes. She is currently head of this laboratory. She is working on tire/road interactions (skid resistance, rolling resistace) and heavy vehicles safety since twelve years. She is participating to several natianal and European research projects (VERTEC, HeavyRoute, Skidsafe, ROSANNE, LCE4RAODS). Lastly, she is deeply involved in european standardization as a french expert in TC227/WG5 ‘surface characteristics’.

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Bouteldja, M., Cerezo, V. Low rate error modeling of articulated heavy vehicle dynamics and experimental validation. Int. J. Control Autom. Syst. 15, 2203–2212 (2017). https://doi.org/10.1007/s12555-016-0033-7

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  • DOI: https://doi.org/10.1007/s12555-016-0033-7

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