22 research outputs found
Sliding Mode Control for Trajectory Tracking of an Intelligent Wheelchair
This paper deal with a robust sliding-mode trajectory tracking controller, fornonholonomic wheeled mobile robots and its experimental evaluation by theimplementation in an intelligent wheelchair (RobChair). The proposed control structureis based on two nonlinear sliding surfaces ensuring the tracking of the three outputvariables, with respect to the nonholonomic constraint. The performances of theproposed controller for the trajectory planning problem with comfort constraint areverified through the real time acceleration provided by an inertial measurement unit
Trajectory tracking and traction coordinating controller design for lunar rover based on dynamics and kinematics analysis
Trajectory tracking control is a necessary part for autonomous navigation of planetary rover and traction coordinating control can reduce the forces consumption during navigation. As a result, a trajectory tracking and traction coordinating controller for wheeled lunar rover with Rocker Bogie is proposed in the paper. Firstly, the longitudinal dynamics model and the kinematics model of six-wheeled rover are established. Secondly, the traction coordinating control algorithm is studied based on sliding mode theory with improved exponential approach law. Thirdly, based on kinematics analysis and traction system identification, the trajectory tracking controller is designed using optimal theory. Then, co-simulations between ADAMS and MATLAB/Simulink are carried out to validate the proposed algorithm, and the simulation results have confirmed the effectiveness of path tracking and traction mobility improving
A Comparison Between Coupled and Decoupled Vehicle Motion Controllers Based on Prediction Models
In this work, a comparative study is carried out with two different predictive controllers that consider the longitudinal jerk and steering rate change as additional parameters, as additional parameters, so that comfort constraints can be included. Furthermore, the approaches are designed so that the effect of longitudinal and lateral motion control coupling can be analyzed. This way, the first controller is a longitudinal and lateral coupled MPC approach based on a kinematic model of the vehicle, while the second is a decoupled strategy based on a triple integrator model based on MPC for the longitudinal control and a double proportional curvature control for the lateral motion control. The control architecture and motion planning are exhaustively explained. The comparative study is carried out using a test vehicle, whose dynamics and low-level controllers have been simulated using the realistic simulation environment Dynacar. The performed tests demonstrate the effectiveness of both approaches in speeds higher than 30 km/h, and demonstrate that the coupled strategy provides better performance than the decoupled one. The relevance of this work relies in the contribution of vehicle motion controllers considering the comfort and its advantage over decoupled alternatives for future implementation in real vehicles.This work has been conducted within the ENABLE-S3 project that has
received funding from the ECSEL Joint Undertaking under Grant Agreement
No 692455. This work was developed at Tecnalia Research & Innovation
facilities supporting this research
Trajectory planning of a quadrotor to monitor dependent people
This article introduces a framework for assisting dependent people at home through a vision-based autonomous unmanned aerial vehicle (UAV). Such an aircraft equipped with onboard cameras can be useful for monitoring and recognizing a dependent's activity. This work is focused on the problem of planning the flight path of a quadrotor to perform monitoring tasks. The objective is to design a trajectory planning algorithm that allows the UAV to position itself for the sake of capturing images of the dependent person's face. These images will be later treated by a base station to evaluate the persons emotional state, together with his/her behavior, this way determining the assistance needed in each situation. Numerical simulations have been carried out to validate the proposed algorithms. The results show the effectiveness of the trajectory planner to generate smooth references to our previously designed GPI (generalized proportional integral) controller. This demonstrates that a quadrotor is able to perform monitoring flights with a high motion precision.- This work has been partially supported by Spanish Ministerio de Ciencia, Innovacion y Universidades, Agencia Estatal de Investigacion (AEI)/European Regional Development Fund (FEDER, UE) under DPI2016-80894-R grant. Lidia M. Belmonte holds FPU014/05283 scholarship from Spanish Ministerio de Educacion y Formacion Profesional
Comparison of two non-linear model-based control strategies for autonomous vehicles
This paper presents the comparison of two nonlinear model-based control strategies for autonomous cars. A control oriented model of vehicle based on a bicycle model is used. The two control strategies use a model reference approach. Using this approach, the error dynamics model is developed. Both controllers receive as input the longitudinal, lateral and orientation errors generating as control outputs the steering angle and the velocity of the vehicle. The first
control approach is based on a non-linear control law that is designed by means of the Lyapunov direct approach. The second approach is based on a sliding mode-control that defines a set of sliding surfaces over which the error trajectories will converge. The main advantage of the sliding-control technique is the robustness against non-linearities and parametric uncertainties in the model. However, the main drawback of first ordersliding mode is the chattering, so it has been implemented a high order sliding mode control. To test and compare the proposed control strategies, different path following scenarios are used in simulation.Postprint (published version
Adaptive Steering Control for Autonomous Lane Change Maneuver
International audienceIn this paper, we present a two-layer nonlinear adaptive steering controller for autonomous lane change maneuver with respect to a stopped vehicle. First, we derive a dynamic model of the vehicle using the Boltzmann-Hamel method in quasi-coordinates for nonholonomic systems. The lane change maneuver is investigated as a tracking problem with respect to desired cycloidal trajectory, which is generated in real time. An adaptive update control law is designed that allows tracking the desired trajectories in the presence of unknown inertial parameters of the vehicle. Simulation results illustrate the performance of the proposed controller.Dans cet article, nous prÃĐsentons un contrÃīleur non linÃĐaire à deux couches pour la commande de direction adaptative pour des manÅuvres de changement de voie autonome en dÃĐpassement d'un vÃĐhicule à l'arrÊt. Tout d'abord, nous tirons une modÃĻle dynamique du vÃĐhicule à l'aide d'une mÃĐthode quasi-coordonnÃĐes pour les systÃĻmes non holonomes de Boltzmann-Hamel. La manÅuvre de changement de voie est ÃĐtudiÃĐe en tant que problÃĻme de suivi d'une trajectoire cycloÃŊdale souhaitÃĐe, qui est gÃĐnÃĐrÃĐe en temps rÃĐel. Une loi de commande adaptative est conçue de maniÃĻre permettre le suivi des trajectoires dÃĐsirÃĐes, en prÃĐsence de des paramÃĻtres inertiels inconnues du vÃĐhicule. Des rÃĐsultats de simulation sont prÃĐsentÃĐs afin d'illustrer les performances du dispositif de commande proposÃĐ
Fuzzy logic techniques for Cybercars: a control and decision approach.
National audienceIn the context of Intelligent Transportation Systems (ITS) one of the aims is to reach autonomous vehicle capabilities based on human driver experiences in different situations. This problem can be treated from two points of view: by tracking a reference (curve lines -lateral control- or speed -longitudinal control-) and by the decision approach (in specific or dangerous situations). In this paper, fuzzy logic techniques have been implemented in real time control tools to translate human knowledge to driverless control processes, considering risk/warning situation. A comparison with previous works (based in classic control laws) for driving, was carried out in urban areas. Moreover, a new approach to give the driver, a reference speed when the vehicle is arriving to a traffic light intersection was developed. Some simulations show that fuzzy logic techniques are promising in the development of ITS applications
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And therefore, the characteristics of steering is analyzed in order to design dynamic equation.  Regarding tractorâs path tracking control, there are various significant factors related such as the creation process of parth trajectory which is similar to variety forms of road for tractor to reach the regulated path. Another factor for effective autonomous steering is controlling system which is similar to tractor driver. One of the system applied for steering control is Fuzzy Logic System. Advantage characteristics of the system is its logical reasoning which is consistent with humanâs logical decision. The system possesses an ability to understand a circumstance by if-then translation and to decide among ambiguous situation which is not only yes or no consideration.   However, learning process of Fuzzy Logic System cannot modify the structure of rules and variables by itself. Therefore, another controlling system called Neural Network is applied. Neural Network possesses an ability to learn by pattern recognition and by inductive thinking in the same way as human does.   Fuzzy Logic System and Neural Network are fused to be Neuro-Fuzzy System which is applied for a better effective autonomous steering of tractor studied.Keyword: Fuzzy logic, Neural network, Path tracking, Dynamic equation, Tracto