LPV methods for fault-tolerant vehicle dynamic control

International audienceThis paper aims at presenting the interest of the Linear Parameter Varying methods for vehicle dynamics control, in particular when some actuators may be in failure. The cases of the semi-active suspension control problem and the yaw control using braking, steering and suspension actuators will be presented. In the first part, we will consider the semi-active suspension control problem, where some sensors or actuator (damper leakage) faults are considered. From a quarter-car vehicle model including a non linear semi-active damper model, an LPV model will be described, accounting for some actuator fault represented as some varying parameters. A single LPV fault-tolerant control approach is then developed to manage the system performances and constraints. In the second part the synthesis of a robust gain-scheduled H1 MIMO vehicle dynamic stability controller (VDSC), involving front steering, rear braking, and four active suspension actuators, is proposed to improve the yaw stability and lateral performances. An original LPV method for actuator coordination is proposed, when the actuator limitations and eventually failures, are taken into account. Some simulations on a complex full vehicle model (which has been validated on a real car), subject to critical driving situations (in particular a loss of some actuator), show the efficiency and robustness of the proposed solution

Design of Fault-Tolerant Control for Trajectory Tracking

International audienceThe paper proposes a fault-tolerant integrated control system with the brake and the steering for developing a driver assistance system. The purpose is to design a fault-tolerant control which is able to guarantee the trajectory tracking and lateral stability of the vehicle against actuator fault scenarios. Since both actuators affect the lateral dynamics of the vehicle, in the control design a balance and priority between them must be achieved. The method is extended with a fault-tolerant feature based on a robust LPV method, into which the detected fault information are incorporated. The control design is performed by using the Matlab/Simulink software and the verification of the designed controller is performed by using the CarSim software

Nemleneáris rendszerek irányítási célú identifikációja és járműdinamikai alkalmazásai = Identification for control of nonlinear vehicle systems

A kutatás elsődleges célkitűzése volt a folytonos idejű nemlineáris állapotegyenletekkel leírt modellekben szereplő paramétereknek bemenet-kimenet mérési adatok segítségével történő becslése, az úgynevezett grey-box identifikációs probléma megoldása. Kutatásaink során a folytonos idejű lineáris változó paraméterű (LPV) modelleken alapuló szürkedoboz (grey-box) paraméterbecslési probléma megoldására fókuszáltunk és különös tekintettel olyan kérdések megválaszolására, mint az ismeretlen kezdeti érték által okozott bizonytalanság kiküszöbölése vagy a mintavételezési idő hatása az identifikációs eljárás konvergenciájára. A folytonos idejű szürke doboz modell ismeretlen paramétereinek becslésére egy megfigyelő alapú identifikációs módszert javasoltunk, ami a kezdeti értékek becslésében lévő hibákra kevésbé érzékeny. A kutatás további célja volt, hogy a kidolgozandó alapkutatási eredményeket mint az identifikálhatóságra és konvergens identifikáló eljárásokra vonatkozó vizsgálatokat a járműdinamikai alkalmazások speciális igényei által meghatározott feladatok megoldása során hasznosítsuk. Itt elsősorban rendszer irányítási célú folytonos idejű nemlineáris modellek megadása és ismeretlen komponenseinek identifikálása állt a kutatások középpontjában. | Our primary goal was to elaborate methods for the parameter estimation of continuous time nonlinear models based on input-output measurement data. The parameter estimation of Linear Parameter Varying (LPV) modeling based on a grey-box identification method was in our focus. Since the initial conditions of the nonlinear modeling and the sampling time are crucial for a sufficiently accurate estimation, the effects of these factors were analyzed. An observer-based method for the continuous-time LPV models was designed, since this method was less sensitive to the initial conditions of the nonlinear modeling. Identifiability and the convergence problems were also investigated. This estimation paradigm was applied in various vehicle dynamics applications in order to estimate the unknown or uncertain components in a continuous-time LPV model

Road Quality Information Based Adaptive Semi-active Suspension Control

This paper introduces an adaptive semi-active suspension control by considering global positioning system-based and historical road information. The main idea of this study is to find a corresponding trade-off between comfort and stability at different road irregularities. The introduced semi-active controller is designed based on the Linear Parameter-Varying framework. The behavior of the designed controller can be modified by the use of a scheduling variable. This scheduling variable is selected by considering the various road category. TruckSim simulation environment is used in order to validate the introduced adaptive semi-active suspension control system by comparing it with the non-adaptive scenario. The results show that both driving comfort and vehicle stability have been improved with the proposed adaptive semi-active suspension control

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

An LPV-Based Online Reconfigurable Adaptive Semi-Active Suspension Control with MR Damper

International audienceThis study introduces an online reconfigurable road-adaptive semi-active suspension controller that reaches the performance objectives with satisfying the dissipativity constraint. The concept of the model is based on a nonlinear static model of the semi-active Magnetorheological (MR) damper with considering the bi-viscous and hysteretic behaviors of the damper. The input saturation problem has been solved by using the proposed method in the literature that allows the integration of the saturation actuator in the initial system to create a Linear Parameter Varying (LPV) system. The control input meets the saturation constraint; therewith, the dissipativity constraint is fulfilled. The online reconfiguration and adaptivity problem is solved by using an external scheduling variable that allows the trade-off between driving comfort and road holding/stability. The control design is based on the LPV framework. The proposed adaptive semi-active suspension controller is compared to passive suspension and Bingham model with Simulink simulation, and then the adaptivity of the controller is validated with the TruckSim environment. The results show that the proposed LPV controller has better performance results than the controlled Bingham and passive semi-active suspension model