Model Predictive Control Allocation of Systems with Different Dynamics

International audienceSeveral systems are integrated in passenger cars. Some of them are just redundant systems due to safety requirements. Others, are completely different and can interact with each other as long as they are operating inside the same vehicle. Control allocation methods have been successfully implemented in advanced aircrafts to avoid conflicts, especially in the context of redundant systems. In this paper, we will rather focus on coordinating non-redundant advanced chassis systems with different dynamics. This difference in dynamics can be especially problematic when systems exhibit different communication delays. Model Predictive Control Allocation (MPCA) methods are therefore investigated in order to activate the right system at the right moment. Results show that particularly when the most effective system is saturated, another system with a different time delay can be activated few steps before saturation to instantly take over the maneuver. With good knowledge of actuator dynamics and higher computation power, MPCA methods are able to solve complex problems in severe situations

Adaptive Robust Vehicle Motion Control for Future Over-Actuated Vehicles

International audienceMany challenges still need to be overcome in the context of autonomous vehicles. These vehicles would be over-actuated and are expected to perform coupled maneuvers. In this paper, we first discuss the development of a global coupled vehicle model, and then we outline the control strategy that we believe should be applied in the context of over-actuated vehicles. A gain-scheduled H ∞ controller and an optimization-based Control Allocation algorithms are proposed. High-fidelity co-simulation results show the efficiency of the proposed control logic and the new possibilities that could offer. We expect that both car manufacturers and equipment suppliers would join forces to develop and standardize the proposed control architecture for future passenger cars

Coordination Optimale des Systèmes Châssis pour le Contrôle du Mouvement des Voitures

A large interest has been given recently to global chassis control. One of the main reasons for this would be the approach of fully autonomous vehicles. These vehicles, especially the SAE (J3016) level 5 of automation, are expected to replace the human driver in all situations. The automated vehicle should be able to manage coupled situations in harmony where longitudinal control, lateral control, and eventually vertical control are involved. To do so, the vehicle has more than one embedded system per control axis. Equipment suppliers and new entering automotive actors are continually proposing new solutions to satisfy a specific performance required from future passenger cars. Consequently, the car manufacturer has to coordinate different subsystems coming from different stakeholders to ensure a safe and comfortable driving experience. Until these days, car manufactures favoured simple solutions consisting on adding a coordination layer downstream the competing subsystems in order to mitigate eventual conflicts. Most of strategies adopted consist on prioritizing one system over another depending on predictable conflicting scenarios. Autonomous vehicles need additional subsystems to operate safely. Interactions between these subsystems will increase to the point of becoming unpredictable. This thesis focus on the coordination approach that should be adopted by future vehicles. Particularly, the coordination layer is moved upstream the standalone subsystems to ensure an optimal control distribution. This layer acts as a supervisor depending on optimization-based control allocation algorithms. The control synthesis is based on robust control theories to face environmental changes and the vehicle’s parameters and dynamics uncertainties. Results showed first that even regarding today’s vehicles, the upstream approach can offer additional advantages when it comes to multiple objectives problems solving. In addition, the upstream approach is able to coordinate subsystems of vehicles with a higher over-actuation. Fault-tolerance can be ensured between completely different chassis systems, and qualitative objectives, if rigorously formalized, can be satisfied. The more numerous subsystems will get in the future, the more relevant the upstream approach would become to vehicle motion control. We expect that the important benefits shown in this thesis thanks to an optimal upstream coordination approach would encourage car manufacturers and equipment to switch towards more open solutions, propose together the necessary standardizations, and accelerate the autonomous vehicles development.Le contrôle global du châssis a fait récemment l'objet d'une attention particulière. Cela serait motivé surtout par l’approche des véhicules entièrement autonomes. Ces véhicules, en particulier le niveau 5 d’automatisation SAE (J3016), devraient remplacer le conducteur humain dans presque toutes les situations. Le véhicule automatisé devrait être capable de gérer en harmonie des situations couplées où sont intégrés le contrôle longitudinal, latéral et éventuellement vertical. Pour ce faire, le véhicule dispose de plusieurs systèmes intégrés par axe de contrôle. En effet, les équipementiers automobiles et les nouveaux acteurs de l'industrie automobile proposent continuellement de nouvelles solutions pour satisfaire des performances bien spécifiques. Le constructeur automobile doit quant à lui coordonner différents sous-systèmes provenant de différentes parties prenantes afin de garantir une expérience de conduite fiable et confortable. Jusqu'à présent, les constructeurs automobiles privilégiaient des solutions simples consistant à ajouter une couche de coordination en aval des sous-systèmes concurrents afin de limiter les potentiels conflits. La plupart des stratégies adoptées consistent à prioriser un système par rapport à un autre en fonction de certains scénarios conflictuels prévisibles. Les véhicules autonomes ont besoin de sous-systèmes supplémentaires pour fonctionner en toute sécurité. Ainsi, les interactions entre les sous-systèmes s'amplifieront au point de devenir imprévisibles. Cette thèse met l'accent sur l'approche de coordination qui devrait être adoptée par les véhicules du futur. En particulier, la couche de coordination est déplacée en amont des sous-systèmes autonomes pour assurer une distribution de commande optimale. Cette couche agit comme un superviseur basé sur des algorithmes d'allocation optimale du contrôle. La synthèse des correcteurs repose sur les théories du contrôle robuste permettant de faire face aux changements environnementaux et aux incertitudes paramétriques et dynamiques du véhicule. Les résultats ont d’abord montré que même en ce qui concerne les véhicules actuels, l’approche en amont peut offrir des avantages supplémentaires pour ce qui est de la résolution de problèmes à objectifs multiples. En outre, l’approche en amont permet de coordonner les sous-systèmes des véhicules présentant une sur-actionnement plus élevé. La tolérance aux pannes peut être assurée entre des systèmes de châssis complètement différents, et des objectifs qualitatifs, s'ils sont rigoureusement formalisés, peuvent être satisfaits. Plus les sous-systèmes seront nombreux à l'avenir, plus l'approche en amont deviendrait pertinente pour le contrôle du mouvement des véhicules. Nous espérons que les avantages conséquents présentés dans cette thèse grâce à une approche de coordination en amont optimale encourageraient les constructeurs automobiles et leurs équipementiers à opter pour des solutions plus ouvertes, à proposer ensemble les normalisations nécessaires et accélérer ainsi le développement des véhicules autonomes

Optimization-Based Control Allocation for Driving Braking Torque Vectoring in a Race Car

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Robust Control for Over-Actuated Vehicles

International audienceMany car manufacturers are equipping their vehicles with advanced systems to win the race towards autonomous vehicles. In order to ensure multiple objectives, different embedded systems influencing differently the same physical variable are often implemented in the same vehicle. Most of car manufacturers tend to activate one system at a time, especially when the low-level control of actuators is developed by different equipment suppliers, making the inner dynamics uncertain. However, this limits the potential of the vehicle. This paper discusses the feasibility of coordinating these systems when activated at the same time, while ensuring an acceptable robustness regarding the uncertain dynamics. Results showed good performance in severe maneuvers when combining robust control synthesis and optimization-based control allocation algorithms. Therefore, several embedded systems may be activated at the same time to expand the overall potential of the vehicle and deal with more difficult situations

Optimal Coordination of Chassis Systems in Simultaneous Operations

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