Research On Several Key Problems Of Motion Control For Nonholonomic Mobile Robot

Due to nonholonomic constraints and high nonlinearity of nonholonomic mobile robot, it is challenging to do some research on robot motion control. Besides, how to deal with this problem has a great impact on working performance. Hence, research on motion control is important and valuable in theory and practice. This paper takes nonholonomic mobile robot as the researching object, considers kinematic and dynamic model of the robot and refers to fuzzy, sliding mode, Backstepping technique and so on. It does some in-depth research on the motion control including path tracking, trajectory tracking, point stabilization, and combination of trajectory tracking and point stabilization deeply. The main contents are as follow:1. A path tracking control law is proposed by integrating fuzzy and PI methods. By introducing threshold, this law is divided into two parts: approaching phase and stable phase. The former employs the fuzzy control to track reference path and the later utilizes PI control to diminish the tracking error.2. A solution for the trajectory tracking of mobile robot is presented by using sliding mode control and neural dynamics. Based on velocity control, an asymptotic stable torque controller is designed and chattering phenomenon is reduced by using variable rate function. In order to solve the speed and torque jump problem, a neural dynamic model is integrated into the control law.3. A fuzzy point stabilization method is proposed for the mobile robot moving on uneven surface. Referring to fuzzy theory, linear torque controller and angular torque controller of the robot are designed to realize the point stabilization from any point to any point.4. A mixed controller for solving the trajectory tracking and point stabilization problems of a mobile robot is presented, applying the integration of Backstepping technique and neural dynamics. By introducing a virtual target point, the whole motion process is divided into two parts. The first one is employed to realize tracking control and the other one is adopted to implement point stabilization. Moreover, to solve the speed and torque jump problems and make the controller generate smooth and continuous signal when controllers switch, the neural dynamics model is integrated into the Backstepping.