Static output feedback control for lane change maneuver

International audienceThis paper addresses the lateral control of a vehicle during lane change maneuvers. The proposed design procedure aims to answer the questions of control using cost-effective sensors implementation, adaptation to measured variables and robustness to unmeasured varying parameters. This is achieved through a static output feedback controller with preview information. The only used measurements are the lateral displacement at sensor location and the yaw angle relative to the lane centerline. The vehicle lateral model is augmented with an integral action, the error signal and the preview reference signal. The controller is synthesized using the LMI framework thanks to a relaxation method that removes the nonlinear terms. Simulations are conducted for various scenarios showing the ability of the design method to handle different performance objectives

Force feedback stabilization for remote control of an assistive mobile robot

International audienceIn this paper, we consider a bilateral control of an assistive mobile robot over communication channels with constant/variable time delays. The mobile robot is used for exploring a domestic environment. The main purpose of the present work is to help the human in controlling better the slave robot. In addition, the proposed control scheme improves the operator perception of the remote environment. The human-operator can actively control the mobile robot, using its intrinsic sensors, and ''feel" the robot's environment. The haptic device is used like a joystick and controls the linear velocity and heading angle of the mobile robot. Many experiments have been performed to validate the proposed control scheme, and to show, in the same time, the importance of the force feedback in such applications and accessibility situations : doorways, obstacle exploration, wall tracking, etc

Lateral & Steering Dynamics Estimation for Single Track Vehicle: Experimental Tests * *This work is supported by National Agency of Research under the framework VIROLO++.

International audienceThis paper deals with lateral and steering dynamics estimation of powered two-wheeled (PTW) vehicles. It presents an experimental validation of the Unknown Input Observer (UIO) addressed in Damon et al. (2016). A small scooter equipped with a multi-sensor architecture used to performed the test is introduced. A mathematical model of the scooter is derived using measured parameters on a Computer-Aided Design (CAD) model. Then the main design steps of the UIO are shortly remind. Finally, an urban driving scenario is presented to show the effectiveness of the proposed observer to estimate the lateral dynamics and the rider's action in real riding scenario

Road Geometry and Steering Reconstruction for Powered Two Wheeled Vehicles

International audienceThis paper deals with the estimation of both motorcycle lateral dynamics and road geometry reconstruction. A linear parameter varying (LPV) unknown input observer is designed to estimate the whole motorcycle dynamic states including road banking angles and the rider's steering torque taken into account the variation of the forward velocity. The road bank angle and the lateral slip angle are relevant parameters for improving rider's safety and handling, thus, it is interesting to estimate the road geometry. The observer convergence study is based on Lyapunov theory and the established convergence conditions are expressed in linear matrix inequalities (LMIs) formalism. The main idea consists in getting a set of conditions to design an observer transformed into a polytopic form, which estimates a part of the motorcycle dynamics states independently of some inputs (rider torque) and/or other states (zeros dynamics: roll angle) taken into account the variation of the longitudinal velocity

Motorcycle Riding Simulator: How to Estimate Robustly the Rider's Action

International audienceThis paper deals with a motorcycle riding simulator and addresses two key issues: 1) reconstruction of rider's action, considered as the main input to the simulation system and 2) design an appropriate force feedback, on the handlebar, emulating a tire-road contact. To answer the first challenge, a Walcott-Zak based sliding-mode observer is designed for the rider torque estimation. The reconstructed torque is used as the main control of the virtual motorcycle dynamic model, in order to actuate the simulator's platform. The steering system is modeled as a haptic display subjected to a couple of action-reaction torques: rider and tire-road dynamics. Besides, a torque feedback is implemented to compensate the lack of the real tire-road contact. The control approach is based on a robust tracking problem of a reference steering angle by using $\mathcal{H}_\infty$ optimization technique

Force feedback control based on VGSTA for single track riding simulator

International audienceA direct application of the variable-gain super-twisting algorithm (VGSTA) is implemented for torque feedback on a handlebar of a riding simulator. This control strategy aims to compensate perturbations changing with the system states. Thanks to the good tracking performance and robustness/insensitiveness of such a control method, a precise estimation of the rider's torque applied on the riding simulator handlebar is possible. A first-order sliding-mode observer with stabilization is designed for the estimation of the unknown input rider action. Experimental implementation and analysis are provided to point-out the effectiveness of the proposed approach

Powered Two-Wheeled Vehicles Steering Behavior Study: Vision-Based Approach

International audienceThis paper presents a vision-based approach to prevent dangerous steering situations when riding a motorcycle in turn. In other words, the proposed algorithm is capable of detecting under, neutral or over-steering behavior using only a conventional camera and an inertial measurement unit. The inverse perspective mapping technique is used to reconstruct a bird-eye-view of the road image. Then, filters are applied to keep only the road markers which are, afterwards, approximated with the well-known clothoid model. That allows to predict the road geometry such that the curvature ahead of the motorcycle. Finally, from the predicted road curvature, the measures of the Euler angles and the vehicle speed, the proposed algorithm is able to characterize the steering behavior. To that end, we propose to estimate the steering ratio and we introduce new pertinent indicators such that the vehicle relative position dynamics to the road. The method is validated on the advanced simulator BikeSim during a steady turn