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.

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.

An Iterative Learning Control for Uncertain Systems Using Structured Singular Value

1999 ◽  
Vol 121 (4) ◽  
pp. 660-667 ◽  
Author(s):  
Tae-Yong Doh ◽  
Jung-Ho Moon ◽  
Myung Jin Chung
Keyword(s):  
Robust Stability ◽  
Iterative Learning Control ◽  
Design Method ◽  
Learning Control ◽  
Convergence Condition ◽  
Singular Value ◽  
Iterative Learning ◽  
Structured Singular Value ◽  
Plant Uncertainty ◽  
Uncertain Linear Systems

To deal with an iterative learning control (ILC) system with plant uncertainty, a set of new terms related with robust convergence is first defined. This paper proposes a sufficient condition for not only robust convergence but also robust stability of ILC for uncertain linear systems, including plant uncertainty. Thus, to find a new condition unrelated to the uncertainty, we first separate it into a known part and uncertainty one using linear fractional transformations (LFTs). Then, robust convergence and robust stability of an ILC system is determined by structured singular value (μ) of only the known part. Based on the novel condition, a learning controller and a feedback controller are developed at the same time to ensure robust convergence and robust stability of the ILC system under plant uncertainty. Lastly, the feasibility of the proposed convergence condition and design method are confirmed through computer simulation on an one-link flexible arm.

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