河北建筑工程学院毕业设计（论文）外文资料翻译 系别： 机 械 工 程 系 专业： 机械设计制造及其自动化 班级： 机083班 姓名： 王晓良 学号： 2008307335 外文出处：Proceedings ofthe 1998 IEEEInternational Conference on Robotics & Automation 附 件：1、外文原文；2、外文资料翻译译文。指导教师评语：签字： 年 月 日Proceedings ofthe 1998 IEEEInternational Conference on Robotics & AutomationLeuven, Belgium May 199813A practical approach to feedback control for a mobile robot with trailerF. Lamiraux and J.P. LaumondLAAS-CNRSToulouse, Franceflorent ,jpllaas.frAbstractThis paper presents a robust method to control a mobile robot towing a trailer. Both problems of trajectory tracking and steering to a given configuration are addressed. This second issue is solved by an iterative trajectory tracking. Perturbations are taken into account along the motions. Experimental results on the mobile robot Hilare illustrate the validity of our approach.1 IntroductionMotion control for nonholonomic systems have given rise to a lot of work for the past 8 years. Brocketts condition 2 made stabilization about a given configuration a challenging task for such systems, proving that it could not be performed by a simple continuous state feedback. Alternative solutions as time-varying feedback l0, 4, 11, 13, 14, 15, 18 or discontinuous feedback 3 have been then proposed. See 5 for a survey in mobile robot motion control. On the other hand, tracking a trajectory for a nonholonomic system does not meet Brocketts condition and thus it is an easier task. A lot of work have also addressed this problem 6, 7, 8, 12, 16 for the particular case of mobile robots.All these control laws work under the same assumption: the evolution of the system is exactly known and no perturbation makes the system deviate from its trajectory.Few papers dealing with mobile robots control take into account perturbations in the kinematics equations. l however proposed a method to stabilize a car about a configuration, robust to control vector fields perturbations, and based on iterative trajectory tracking.In this paper, we propose a robust scheme based on iterative trajectory tracking, to lead a robot towing a trailer to a configuration. The trajectories are computed by a motion planner described in 17 and thus avoid obstacles that are given in input. In the following.We wont give any development about this planner,we refer to this reference for details. Moreover,we assume that the execution of a given trajectory is submitted to perturbations. The model we chose for these perturbations is very simple and very general.It presents some common points with l.The paper is organized as follows. Section 2 describes our experimental system Hilare and its trailer:two hooking systems will be considered (Figure 1).Section 3 deals with the control scheme and the analysis of stability and robustness. In Section 4, we present experimental results.The presence of obstacle makes the task of reaching a configuration even more difficult and require a path planning task before executing any motion. 2 Description of the systemHilare is a two driving wheel mobile robot. A trailer is hitched on this robot, defining two different systems depending on the hooking device: on system A, the trailer is hitched above the wheel axis of the robot (Figure 1, top), whereas on system B, it is hitched behind this axis (Figure l , bottom). A is the particular case of B, for which = 0. This system is however singular from a control point of view and requires more complex computations. For this reason, we deal separately with both hooking systems. Two motors enable to control the linear and angular velocities （，) of the robot. These velocities are moreover measured by odometric sensors, whereas the angle between the robot and the trailer is given by an optical encoder. The position and orientation（,）of the robot are computed by integrating the former velocities. With these notations, the control system of B is: （1） Figure 1: Hilare with its trailer3 Global control scheme3.1 MotivationWhen considering real systems, one has to take into account perturbations during motion execution.These may have many origins as imperfection of the motors, slippage of the wheels, inertia effects . These perturbations can be modeled by adding a term in the control system (l),leading to a new system of the formwhere may be either deterministic or a random variable.In the first case, the perturbation is only due to a bad knowledge of the system evolution, whereas in the second case, it comes from a random behavior of the system. We will see later that this second model is a better fit for our experimental system.To steer a robot from