Please use this identifier to cite or link to this item:
Title: Development of intelligent learning motion control systems
Authors: ZHAO SHAO
Keywords: Motion Control, Force Ripple Compensation, Intelligent Learning Control, Time Delay, Linear Motor, PID Tuning
Issue Date: 16-Jan-2006
Citation: ZHAO SHAO (2006-01-16). Development of intelligent learning motion control systems. ScholarBank@NUS Repository.
Abstract: Modern mechanical systems need precision motion control to achieve good positioning/tracking performance at high speed and high accuracy. Therefore, the requirements on motion control systems become more and more stringent. In this thesis, intelligent learning control algorithms are developed to achieve better positioning/tracking performance in motion control systems. Firstly, an adaptive control algorithm is presented to suppress the force ripples in Permanent Magnet Linear Motors (PMLMs). Then, an Iterative Learning Control (ILC) scheme, a model-free approach, is proposed to compensate the friction and force ripples in the linear motors to achieve good tracking performance for high precision and repetitive motion control applications. Subsequently, an online automatic tuning method of PID controller based on an ILC approach is presented in this thesis. Following that, a new form of Repetitive Control (RC) approach is proposed which is applicable to time-delay systems for the first time. Finally, a predictive ILC algorithm is developed for time-varying, linear and repetitive systems. In this thesis, extensive simulation and experimental results will be furnished to illustrate the effectiveness of the proposed learning approaches.
Appears in Collections:Ph.D Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
thesisall.pdf3.49 MBAdobe PDF



Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.