Multi-Variable and Multi-Objective Gain-Scheduled Control Based on Youla-Kucera Parameterization: Application to Autonomous Vehicles - Archive ouverte HAL Accéder directement au contenu
Pré-Publication, Document De Travail Année : 2022

Multi-Variable and Multi-Objective Gain-Scheduled Control Based on Youla-Kucera Parameterization: Application to Autonomous Vehicles

Hussam Atoui
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Olivier Sename
Vicente Milanés
John Jairo Martinez Molina

Résumé

This paper presents a new method to interpolate between a set of Linear Parameter-Varying (LPV) controllers, each one being a gain-scheduled of Linear Time-Invariant (LTI) controllers designed separately for different operating points. The gainscheduling is achieved based on Youla-Kucera (YK) parameterization. A generalized LPV-YK control structure is designed to interpolate between various LPV controllers. The closed-loop system is proved to guarantee the quadratic stability for any continuous/discontinuous interpolating signals in terms of a set of Linear Matrix Inequalities (LMIs). The proposed method can help multi-variable and multiobjective systems to achieve high performances at different operating conditions and different critical situations regardless of the interpolation rate. A numerical example is simulated to show the importance of the proposed method to achieve different objectives for lateral control of autonomous vehicles. In addition, the approach has been tested on a real Renault ZOE vehicle to validate its real performance, and compare it with a standard polytopic LPV controller.
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Dates et versions

hal-03762037 , version 1 (26-08-2022)

Identifiants

  • HAL Id : hal-03762037 , version 1

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Hussam Atoui, Olivier Sename, Vicente Milanés, John Jairo Martinez Molina. Multi-Variable and Multi-Objective Gain-Scheduled Control Based on Youla-Kucera Parameterization: Application to Autonomous Vehicles. 2022. ⟨hal-03762037⟩

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