Two-Wheeled Mobile Robot Tracking Based on Iterative Learning Control

2012 ◽  
Vol 433-440 ◽  
pp. 5866-5870 ◽  
Author(s):  
Wu Wang ◽  
Jing Chen ◽  
Lin Mao
Keyword(s):  
Mobile Robot ◽  
Control Strategy ◽  
Iterative Learning Control ◽  
Learning Control ◽  
Convergence Condition ◽  
Iterative Learning ◽  
Wheeled Mobile Robot ◽  
Position Tracking ◽  
Control Laws ◽  
Robot Tracking

The discrete dynamic kinematics models of two-wheeled mobile robot was constructed and iterative learning control strategy was applied into this repeat motion plant, iterative learning controller for mobile robot was designed and the trajectory tracking algorithm was programmed, also the iterative learning control laws was designed and the ultimate simulation study manifest that learning operator can influence it’s iterative learning quality and if the control system unsatisfied with convergence condition, the system will unstable and position tracking divergent, otherwise, the robust control realized.

scholarly journals Discrete PID-Type Iterative Learning Control for Mobile Robot

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Hongbin Wang ◽  
Jian Dong ◽  
Yueling Wang
Keyword(s):  
Mobile Robot ◽  
Iterative Learning Control ◽  
Engineering Application ◽  
Learning Control ◽  
Convergence Condition ◽  
Small Error ◽  
Iterative Learning ◽  
Control Approach ◽  
Certification Procedure ◽  
Nonlinear Discrete System

Through studying tracking problems of the wheeled mobile robot, this paper proposed a discrete iterative learning control approach based on PID with strong adaptability, fast convergence, and small error. This algorithm used discrete PID to filter rejection and restrained the influence of interference and noise on trajectory tracking, which made it more suitable for engineering application. The PID-type iterative learning convergence condition and certification procedure are presented. The results of simulation reveal that the PID-type ILC holds the features of simplicity, strong robustness, and high repeating precision and can well meet the control requirement of nonlinear discrete system.

Trajectory tracking of wheeled mobile robot by adopting iterative learning control with predictive, current, and past learning items

Robotica ◽  
2014 ◽  
Vol 33 (7) ◽  
pp. 1393-1414 ◽  
Author(s):  
Chong Yu ◽  
Xiong Chen
Keyword(s):  
Mobile Robot ◽  
Trajectory Tracking ◽  
Iterative Learning Control ◽  
Control Algorithm ◽  
Mathematical Proof ◽  
Learning Control ◽  
Iterative Learning ◽  
Wheeled Mobile Robot ◽  
State Variables ◽  
Wheeled Mobile Robots

SUMMARYIn this paper, an iterative learning control algorithm is adopted to solve the high-precision trajectory tracking issue of a wheeled mobile robot with time-varying, nonlinear, and strong-coupling dynamics properties. The designed iterative learning control law adopts predictive, current and past learning items to drive the state variables, and input variables, and outputs variables converge to the bounded scope of their desired values. The algorithm can enhance the control performance, stability and robust characteristics. The rigorous mathematical proof of the convergence character of the proposed iterative learning control algorithm is given. The feasibility, effectiveness, and robustness of the proposed algorithm are illustrated by quantitative experiments and comparative analysis. The experimental results show that the proposed iterative learning control algorithm has an outstanding control effect on the trajectory tracking issue of wheeled mobile robots.

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