【正文】
ve been done in Matlab174。+V(q,q)v+G(q)=? (1) Where q=? ??,yx T is the vector of generalized coordinates which describes the robot position, (x,y) are the cartesian coordinates, which denote the mobile center of mass and θ is the angle between the heading direction and the xaxis(which is taken counterclockwise form)。 ). Patricia Melin is with the Division of Graduate Studies and Research in Tijuana Institute of Technology, Mexico ( ). Arnulfo Alanis is with the Division of Graduate Studies and Research in Tijuana Institute of Technology, Mexico ( ) Leslie Astudillo is a graduate student in Computer Science with the Division of Graduate Studies and Research in Tijuana Institute of Technology, Mexico ( ) Jose Soria is a with the Division of Graduate Studies and Research in Tijuana Institute of Technology, Mexico ( ). Luis Aguilar is with CITEDIIPN Tijuana, Mexico() and Drakunov [2] and Chwa [4], used a sliding mode control to the tracking control problem. Fierro and Lewis [5] propose a dynamical extension that makes possible the integration of kinematic and torque controller for a nonholonomic mobile robot. Fukao et al. [7], introduced an adaptive tracking controller for the dynamic model of mobile robot with unknown parameters using backstepping. In this paper we present a tracking controller for the dynamic model of a unicycle mobile robot, using a control law such that the mobile robot velocities reach the given velocity inputs, and a fuzzy logic controller such that provided the required torques for the actual mobile robot. The rest of this paper is organized as follows. Sections II and III describe the formulation problem, which include: the kinematic and dynamic model of the unicycle mobile robot and introduces the tracking controller. Section IV illustrates the simulation results using the tracking controller. The section V gives the conclusions. II. PROBLEM FORMULATION A. The Mobile Robot The model considered is a unicycle mobile robot (see Fig. 1), it consist of two driving wheels mounted on the same axis and a front free wheel [3]. Fig. 1. Fig. 1. Wheeled mobile robot. The motion can be described with equation (1) of movement in a plane [5]: Qamp。 附件 2:外文原 文 Intelligent Control of an Autonomous Mobile Robot using Type2 Fuzzy Logic Abstract— We develop a tracking controller for the dynamic model of unicycle mobile robot by integrating a kinematic controller and a torque controller based on Fuzzy Logic Theory. Computer simulations are presented confirming the performance of the tracking controller and its application to different navigation problems. Index Terms—Intelligent Control, Type2 Fuzzy Logic, Mobile Robots. I. INTRODUCTION Mobile robots are nonholonomic systems due to the constraints imposed on their kinematics. The equations describing the constraints cannot be integrated simbolically to obtain explicit relationships between robot positions in local and global coordinate’s frames. Hence, control problems involve them have attracted attention in the control munity in the last years [11]. Different methods have been applied to solve motion control problems. Kanayama et al. [10] propose a stable tracking control method for a nonholonomic vehicle using a Lyapunov function. Lee et al. [12] solved tracking control using backstepping and in [13] with saturation constraints. Furthermore, most reported designs rely on intelligent control approaches such as Fuzzy Logic Control [1][8][14][17][18][20] and Neural Networks [6][19]. However the majority of the publications mentioned above, has concentrated on kinematics models of mobile robots, which are controlled by the velocity input, while less attention has been paid to the control problems of nonholonomic dynamic systems, where forces and torques are the true inputs: Bloch Manuscript received December 15, 2020 qnd accepted on April 5, 2020. This work was supported in part by the Research Council of DGEST un