Some remarks on wheeled autonomous vehicles and the evolution of their control design

Recent investigations on the longitudinal and lateral control of wheeled autonomous vehicles are reported. Flatness-based techniques are first introduced via a simplified model. It depends on some physical parameters, like cornering stiffness coefficients of the tires, friction coefficient of the road, ..., which are notoriously difficult to identify. Then a model-free control strategy, which exploits the flat outputs, is proposed. Those outputs also depend on physical parameters which are poorly known, i.e., the vehicle mass and inertia and the position of the center of gravity. A totally model-free control law is therefore adopted. It employs natural output variables, namely the longitudinal velocity and the lateral deviation of the vehicle. This last method, which is easily understandable and implementable, ensures a robust trajectory tracking problem in both longitudinal and lateral dynamics. Several convincing computer simulations are displayed.Comment: 9th IFAC Symposium on Intelligent Autonomous Vehicles (Leipzig, Germany, 29.06.2016 - 01.07.2016

Continuous-Time Switched H∞ Proportional-Integral observer: Application for sideslip and road bank angles estimation

International audience— In this work, a Continuous-Time Switched H ∞ Proportional-Integral (CTSH ∞ PI) observer is presented. The estimation method is based on a proportional-integral observer introduced by [13], [11], [12]. The estimation method is used to estimate simultaneously the state variables and unknown inputs of switched systems. A design method is established using a common Lyapunov function and H ∞ norm. Its stability and global convergence conditions are proved and expressed in term of LMIs. All conditions are established under given switching signals. The estimation method is applied in vehicle dynamics to estimate simultaneously the vehicle sideslip angle and road bank angle. Moreover, the switching signal is deduced from measured premise variables. Simulation tests with experimental data are included to demonstrate the advantage of this method

Commande couplée longitudinale/latérale de véhicules par platitude et estimation algébrique

International audienceThis paper deals with a coupled longitudinal/lateral vehicle nonlinear control and road bank angle estimation. The control law is designed using the differential flatness property of nonlinear longitudinal and lateral vehicle model. An algebraic estimation approach is employed to estimate simultaneously the vehicle dynamic parameters (like lateral forces and roll angle) and unknown inputs (like road bank angle and corrective yaw moment). The control and estimation approaches use also the algebraic estimators to perform the filtering and the numerical derivatives of noisy measurements. To perform some coupled vehicle tasks like an automatic line keeping of straight or curved lines, a line change maneuver, obstacle avoidance, a combined control of longitudinal and lateral vehicle motions is required. Note that this controller is designed via steering angle and traction/braking torque of vehicle. Furthermore, some other parameters like road bank angle has an important influence on vehicle lateral dynamics behavior and control vehicle systems. For this, the algebraic based unknown input estimator is considered here to estimate road bank angle and consider a more realistic trajectories. Interesting results are obtained using real data which are acquired under high lateral accelerations

A new model-free design for vehicle control and its validation through an advanced simulation platform

A new model-free setting and the corresponding "intelligent" P and PD controllers are employed for the longitudinal and lateral motions of a vehicle. This new approach has been developed and used in order to ensure simultaneously a best profile tracking for the longitudinal and lateral behaviors. The longitudinal speed and the derivative of the lateral deviation, on one hand, the driving/braking torque and the steering angle, on the other hand, are respectively the output and the input variables. Let us emphasize that a "good" mathematical modeling, which is quite difficult, if not impossible to obtain, is not needed for such a design. An important part of this publication is focused on the presentation of simulation results with actual and virtual data. The actual data, used in Matlab as reference trajectories, have been obtained from a properly instrumented car (Peugeot 406). Other virtual sets of data have been generated through the interconnected platform SiVIC/RTMaps. It is a dedicated virtual simulation platform for prototyping and validation of advanced driving assistance systems. Keywords- Longitudinal and lateral vehicle control, model-free control, intelligent P controller (i-P controller), algebraic estimation, ADAS (Advanced Driving Assistance Systems).Comment: in 14th European Control Conference, Jul 2015, Linz, Austria. 201

A new LPV/Hinf semi-active suspension control strategy with performance adaptation to roll behavior based on non linear algebraic road profile estimation

International audienceThis paper presents a new LPV/Hinf semi-active suspension control strategy for a commercial vehicle equipped with 4 Magneto-Rheological dampers. The proposed approach concerns road adaptation using on-line road profile identification based on a non linear algebraic observer with unknown input. Then, the suspensions forces distribution in each corner of vehicle is performed considering roll dynamics. In this LPV/H1 strategy, 2 varying parameters are used to model the semi-active behaviour of the MR dampers, and 2 other ones, namely, the road roughness identification and roll dynamics, are considered for the road adaptation and the full vehicle vertical dynamics control. Different ISO road classes are used to test the efficiency of the on-line non linear algebraic road profile identification. Simulations scenarios, applied on a non linear full vehicle model, are used to evaluate the LPV/H1 controller performances in term of passengers comfort and road holding improvement in different driving situations

Coupled nonlinear vehicle control: Flatness-based setting with algebraic estimation techniques

International audienceA combined nonlinear longitudinal and lateral vehicle control is investigated. Flatness-based nonlinear control and new algebraic estimation techniques for noise removal and numerical differentiation are the main theoretical tools. An accurate automatic path-tracking via vehicle steering angle and driving/braking wheel torque is thus ensured. It combines the control of the lateral and longitudinal motions in order to track straight or curved trajectories and to perform a combined lane-keeping and steering control during critical driving situations such as obstacle avoidance, stop-and-go control, lane-change maneuvers or any other maneuvers. Promising results have been obtained with noisy experimental data, which were acquired by a laboratory vehicle with high dynamic loads and high lateral accelerations

Algebraic nonlinear estimation and flatness-based lateral/longitudinal control for automotive vehicles

6 pagesInternational audienceA combined longitudinal and lateral vehicle control is presented. It employs flatness-based control and new algebraic estimation techniques for the numerical differentiation of noisy signals. This nonlinear control is designed for automatic path-tracking via vehicle steering angle and driving/braking wheel torque. It combines the control of the lateral and longitudinal movements in order to ensure an accurate tracking of straight or curved trajectories. It can also be used to perform a combined lane-keeping and steering control during critical driving situations such as obstacle avoidance, stop-and-go control, lane-change maneuvers or any other maneuvers. Promising results have been obtained using the noisy experimental data acquired by a laboratory vehicle under high dynamic loads and characterized by high lateral accelerations

Study and comparison of non linear and LPV control approaches for vehicle stability control

International audienceThis paper proposes a study and a comparison between two efficient and novel vehicle control dynamics strategies, namely, the non linear Flatness control strategy and the LPV/Hinf control strategy. The first one concerns a controller based on the differential algebraic flatness of non linear systems and an algebraic non linear estimation applied to commercial vehicles. The second one is a LPV/Hinf (Linear Varying Parameter with the Hinf norm ) control using a stability monitoring system to achieve the vehicle dynamics control objective. These two strategies use Active Steering and Electro- Mechanical Braking actuators and aim at improving the vehicle stability and steerability by designing a multivariable controller that acts simultaneously on the lateral and longitudinal dynam- ics of the car. Simulations are performed on a complex nonlinear full vehicle model, the same driving scenario is applied for the two control strategies. The model parameters are those of a Renault Mégane Coupé (see table.I), obtained by identification with real data. Promising simulations results are obtained. Comparison between the two proposed strategies and the uncontrolled vehicle show the reliability and the robustness of the proposed solutions, even if one is governed within the linear control framework while the other one is a non linear control approach

Steering control based on a two-level driver model: experimental validation and robustness tests

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Steering vehicle control via robust linear control and non linear control: Experimental evaluation

International audienceThis paper proposes the design and synthesis of three control laws dedicated to vehicle steering control, two robust linear controls and a non linear control, and presents a comparison between them. The two robust linear control laws are composed from a two M PID controllers, M PID for the correction of the lateral deviation and M another PID for the correction of the vehicle yaw angle. These two control laws are settled using a Ziegler-Nichols and a LMI-LQR optimization method respectively. The non linear control for the correction of the lateral deviation is based on a continuous first order sliding mode controller. The different methods are synthesized using a linear bicycle vehicle model with variant parameters. These steering control strategies are designed to simulate the non linear vehicle behaviour under high dynamic demands with a four wheel vehicle model. The steering vehicle controls developed here were validated experimentally using the data acquired by a laboratory vehicle Peugeot 307 developed by INRETS-MA