Tracking and Regulation Control of a Mobile Robot System With Kinematic Disturbances: A Variable Structure-Like Approach

2000 ◽  
Vol 122 (4) ◽  
pp. 616-623 ◽  
Author(s):  
W. E. Dixon ◽  
D. M. Dawson ◽  
E. Zergeroglu
Keyword(s):  
Mobile Robot ◽  
Model Simulation ◽  
Tracking Error ◽  
Kinematic Model ◽  
Parametric Uncertainty ◽  
Variable Structure ◽  
Tracking Errors ◽  
Robot System ◽  
Tracking Controller ◽  
Bounded Disturbances

This paper presents the design of a variable structure-like tracking controller for a mobile robot system. The controller provides robustness with regard to bounded disturbances in the kinematic model. Through the use of a dynamic oscillator and a Lyapunov-based stability analysis, we demonstrate that the position and orientation tracking errors exponentially converge to a neighborhood about zero that can be made arbitrarily small (i.e., the controller ensures that the tracking error is globally uniformly ultimately bounded (GUUB)). In addition, we illustrate how the proposed tracking controller can also be utilized to achieve GUUB regulation to an arbitrary desired setpoint. An extension is also provided that illustrates how a smooth, time-varying control law can be utilized to achieve setpoint regulation despite parametric uncertainty in the kinematic model. Simulation results are presented to demonstrate the performance of the proposed controllers. [S0022-0434(00)00504-9]

Tracking Control of a Nonholonomic Mobile Robot Using Neural Network

2015 ◽  
pp. 631-661 ◽  
Author(s):  
Şahin Yildirim ◽  
Sertaç Savaş
Keyword(s):  
Neural Networks ◽  
Mobile Robot ◽  
Tracking Error ◽  
Back Propagation ◽  
Open Loop ◽  
Tracking Performance ◽  
Back Propagation Algorithm ◽  
Tracking Errors ◽  
Nonholonomic Mobile Robot ◽  
Feed Forward Neural Networks

The goal of this chapter is to enable a nonholonomic mobile robot to track a specified trajectory with minimum tracking error. Towards that end, an adaptive P controller is designed whose gain parameters are tuned by using two feed-forward neural networks. Back-propagation algorithm is chosen for online learning process and posture-tracking errors are considered as error values for adjusting weights of neural networks. The tracking performance of the controller is illustrated for different trajectories with computer simulation using Matlab/Simulink. In addition, open-loop response of an experimental mobile robot is investigated for these different trajectories. Finally, the performance of the proposed controller is compared to a standard PID controller. The simulation results show that “adaptive P controller using neural networks” has superior tracking performance at adapting large disturbances for the mobile robot.

Research on NN-PID Motion Control Technology for a Wheeled Mobile Robot

2012 ◽  
Vol 538-541 ◽  
pp. 2636-2640
Author(s):  
Shi Zhu Feng ◽  
Ming Xu
Keyword(s):  
Mobile Robot ◽  
Motion Control ◽  
Pid Controller ◽  
Mobile Robotics ◽  
Kinematic Model ◽  
Wheeled Mobile Robot ◽  
Control Technology ◽  
Robot System

Robotics is a spiry integral technology of mechanics, electrics and cybernetics. Through systematical study of a wheeled mobile robot, The kinematic model of it is deduced. A Cerebella Model Articulation Controller (CMAC) PID controller was developed to control the motion to accomplish the realistic motions of the wheeled mobile robot system. The experimental is carried out. The results prove the algorithm is correct, and indicate that the design of CMAC-PID controller is a success. The whole research will provide a reference to the study of the mobile robotics.

scholarly journals Adaptive Output Feedback Tracking Controller Design of Stochastic Nonlinear Systems with Parameter Uncertainty for Polynomial Function Growth Conditions

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Long-Chuan Guo
Keyword(s):  
Nonlinear Systems ◽  
Output Feedback ◽  
Controller Design ◽  
Polynomial Function ◽  
Tracking Error ◽  
Parametric Uncertainty ◽  
Growth Conditions ◽  
Stochastic Nonlinear Systems ◽  
Tracking Controller ◽  
Feedback Tracking

This paper mainly focuses on output feedback practical tracking controller design for stochastic nonlinear systems with polynomial function growth conditions. Mostly, there are some studies on output feedback tracking control problem for general nonlinear systems with parametric certainty in existing achievements. Moreover, we extend it to stochastic nonlinear systems with parametric uncertainty and system nonlinear terms are assumed to satisfy polynomial function growth conditions which are more relaxed than linear growth conditions or power growth conditions. Due to the presence of unknown parametric uncertainty, an output feedback practical tracking controller with dynamically updated gains is constructed explicitly so that all the states of the closed-loop systems are globally bounded and the tracking error belongs to arbitrarily small interval after some positive finite time. An example illustrates the efficiency of the theoretical results.

scholarly journals Backstepping Approach for Autonomous Mobile Robot Trajectory Tracking

2016 ◽  
Vol 2 (3) ◽  
pp. 478 ◽  
Author(s):  
Ibari Benaoumeur ◽  
Benchikh Laredj ◽  
Hanifi Elhachimi Amar Reda ◽  
Ahmed-foitih Zoubir
Keyword(s):  
Mobile Robot ◽  
Trajectory Tracking ◽  
Controller Design ◽  
Tracking Errors ◽  
Robust Controller ◽  
Output Tracking ◽  
Robot Trajectory ◽  
Tracking Controller ◽  
Angular Velocities ◽  
The Given

This paper proposes a backstepping controller design for trajectory tracking of unicycle-type mobile robots. The main object of the control algorithms developed is to design a robust output tracking controller. The design of the controller is based on the lyapunov theorem, kinematic tracking controller of an unicycle-like mobile robot is used to provides the desired values of the linear and angular velocities for the given trajectory. A Lyapunov-based stability analysis is presented to guarantee the robot stability of the tracking errors. Simulation and experimental results show the effectiveness of the proposed robust controller in term of accuracy and stability under different load conditions.

Visual Servo Control for Wheeled Robot Trajectory Tracking

2011 ◽  
Vol 346 ◽  
pp. 650-656
Author(s):  
Guang Yan Xu ◽  
Xiao Yan Jia ◽  
Hong Shi ◽  
Jian Guo Cui
Keyword(s):  
Mobile Robot ◽  
Trajectory Tracking ◽  
Sliding Mode ◽  
Kinematic Model ◽  
Variable Structure ◽  
Visual Servo ◽  
Trajectory Tracking Control ◽  
Structure Control ◽  
Robot Trajectory ◽  
Sliding Mode Variable Structure

In this paper, we discussed the trajectory tracking control problem of the kinematic model of wheel mobile robot. Designed an asymptotic stability tracking controller, using visual servo method based on inverse system and sliding mode variable structure control, and proposed a method to measure motion state of a target mobile robot. Simulation results show this method is feasible.

Numerical methods based controller design for mobile robots

Robotica ◽  
2009 ◽  
Vol 27 (2) ◽  
pp. 269-279 ◽  
Author(s):  
Gustavo Scaglia ◽  
Lucía Quintero Montoya ◽  
Vicente Mut ◽  
Fernando di Sciascio
Keyword(s):  
Numerical Methods ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Relative Position ◽  
Controller Design ◽  
Tracking Error ◽  
Kinematic Model ◽  
Experimental Results ◽  
Control Actions

SUMMARYThis paper presents the design of four controllers for a mobile robot such that the system may follow a preestablished trajectory. To reach this aim, the kinematic model of a mobile robot is approximated using numerical methods. Then, from such approximation, the control actions to get a minimal tracking error are calculated. Both simulation and experimental results on a PIONEER 2DX mobile robot are presented, showing a good performance of the four proposed mobile robot controllers. Also, an application of the proposed controllers to a leader robot following problem is shown; in it, the relative position between robots is obtained through a laser.

Path Tracking Control of Micro-Tracked Mobile Robot

2014 ◽  
Vol 644-650 ◽  
pp. 265-271 ◽  
Author(s):  
Jian Gao ◽  
Shi Long Zhang
Keyword(s):  
Mobile Robot ◽  
Tracking Control ◽  
Tracking Error ◽  
Kinematic Model ◽  
Path Tracking ◽  
Positioning Accuracy ◽  
And Control ◽  
Tracked Mobile Robot ◽  
The Given ◽  
Motor Model

The positioning accuracy of tracked mobile robot is low because of sliding in steering process. Taking the micro-tracked mobile robot as the platform, the interface force between tracks and ground was analyzed, and the motor model, kinematic model and dynamic model were established further. A tracking error controller was built based on the tracking error equations, and the co-simulation of mechanical and control system was applied to predict the robot’s trajectory. That controller was applied on a small tracked mobile robot designed by the authors’ laboratory, and the path tracking experiments with and without obstacles had been done. The results show that the robot can accurately track the given path, whether there are obstacles or not.

Adaptive and sliding mode tracking control for wheeled mobile robots with unknown visual parameters

2016 ◽  
Vol 40 (1) ◽  
pp. 269-278 ◽  
Author(s):  
Fang Yang ◽  
Hongye Su ◽  
Chaoli Wang ◽  
Zhenxing Li
Keyword(s):  
Mobile Robots ◽  
Tracking Control ◽  
Visual Servoing ◽  
Sliding Mode ◽  
Tracking Error ◽  
Variable Structure ◽  
Wheeled Mobile Robots ◽  
Trajectory Tracking Control ◽  
Structure Control ◽  
Tracking Controller

The trajectory tracking control problem of dynamic nonholonomic wheeled mobile robots is considered via visual servoing feedback. A novel visual feedback tracking error model is proposed. Its tracking controller is independent of uncalibrated visual parameters by using new methods. This controller consists of two units: one is an adaptive control for compensation of the uncertainties of dynamic parameters, the other is a variable structure control for the interference suppression. In addition, the torque tracking controller is global and smooth, and the chattering phenomenon is eliminated. The asymptotic convergence of tracking errors to equilibrium point is rigorously proved by the Lyapunov method. Simulation and experiment results are provided to illustrate the performance of the control law.

Global robust output feedback tracking control of robot manipulators

Robotica ◽  
2004 ◽  
Vol 22 (4) ◽  
pp. 351-357 ◽  
Author(s):  
W. E. Dixon ◽  
E. Zergeroglu ◽  
D. M. Dawson
Keyword(s):  
Output Feedback ◽  
Tracking Control ◽  
Robot Manipulators ◽  
Tracking Error ◽  
Parametric Uncertainty ◽  
Position Tracking ◽  
Incomplete Model ◽  
Bounded Disturbances ◽  
Position Tracking Control ◽  
Feedback Tracking

This paper addresses the problem of global output feedback, link position tracking control of robot manipulators. Specifically, a robust, Lyapunov-based controller is designed to ensure that the link position tracking error is globally uniformly ultimately bounded despite the fact that only link position measurements are available in the presence of incomplete model information (i.e., parametric uncertainty and additive bounded disturbances).

Active Visual Method for Mobile Robots Localization using Double Freedom Pan-Title

2013 ◽  
Vol 336-338 ◽  
pp. 1053-1058
Author(s):  
Bo Wang ◽  
Xing Guang Qi
Keyword(s):  
Mobile Robot ◽  
Solution Method ◽  
Optical Axis ◽  
Kinematic Model ◽  
Field Of View ◽  
Position Vector ◽  
Dual Quaternion ◽  
Robot System ◽  
Visual Method ◽  
Extrinsic Parameters

For a monocular camera-based mobile robot system,we propose the active visual method for robot localization,based on the double freedom pan-tilt.First,the kinematic model of the mobile robot system of monocular vision is given.Secondly,by controlling the pitch and yaw angles of pan-tilt,the camera optical axis always points to the target geometry center in order to solve the field of view problem.Coordinate system relative pose solution method which based on dual quaternion avoids calculating the singularity and improves the positioning accuracy of mobile robots.Finally,according to pan-tilts feedback angles,extrinsic parameters of the camera,the pose and the position of the camera,the position vector and pose vector of the mobile robot are obtained.

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