A Plant-Inversion based Switched Iterative Learning Control Scheme for a Special Class of Multivariable Systems
Abstract
This paper presents a plant-inversion based Switched Iterative Learning Control (SILC) scheme for a special class of Multi-Input Multi-Output (MIMO) systems for which only one output channel can be accessed at any given time. While Asymptotic Stability (AS), or zero error convergence, is predominantly considered in Iterative Learning Control (ILC), AS cannot be achieved for this class of systems. A weaker condition, bounded convergence, however, can be obtained. With the SILC scheme proposed in this paper, the measurement channels are accessed one at a time in a specific order. Each time an output channel is accessed, bounded convergence of all of the channel errors is achieved by using an ILC algorithm. As the access is switched from one channel to the next, the previously achieved convergent error is brought to a new value due to the change of measurement information, which may or may not be less than the previous one, depending on the structure of the learning matrix. Using the inverse plant dynamics as a learning matrix and as the switching action continues occurring, the bounded convergence tends to zero convergence. Illustrative examples are provided to demonstrate the effectiveness of the proposed SILC scheme and its robustness to modeling uncertainty.
Recommended Citation
H. Li et al., "A Plant-Inversion based Switched Iterative Learning Control Scheme for a Special Class of Multivariable Systems," Proceedings of the ASME 2018 Dynamic Systems and Control Conference (2018, Atlanta, GA), vol. 1, American Society of Mechanical Engineers (ASME), Sep 2018.
The definitive version is available at https://doi.org/10.1115/DSCC2018-9069
Meeting Name
ASME 2018 Dynamic Systems and Control Conference, DSCC2018 (2018: Sep. 30-Oct. 3, Atlanta, GA)
Department(s)
Mechanical and Aerospace Engineering
Research Center/Lab(s)
Intelligent Systems Center
Keywords and Phrases
Asymptotic stability; Errors; Feedback control; Human robot interaction; Inverse problems; Iterative methods; Learning algorithms; Machine design; Matrix algebra; MIMO systems; Robotics; Uncertainty analysis; Bounded convergence; Iterative learning control (ILC); Measurement channels; Measurement information; Model uncertainties; Multi-input multi-output system; Specific ordering; Two term control systems
International Standard Book Number (ISBN)
978-0-7918-5189-0
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2018 American Society of Mechanical Engineers (ASME), All rights reserved.
Publication Date
01 Sep 2018