Gain-Scheduled Sliding-Mode-Type Iterative Learning Control Design for Mechanical Systems

Qijia Yao, Hadi Jahanshahi, Stelios Bekiros, Sanda Florentina Mihalache () and Naif D. Alotaibi
Additional contact information
Qijia Yao: School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081, China
Hadi Jahanshahi: Department of Mechanical Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada
Sanda Florentina Mihalache: Automatic Control, Computers & Electronics Department, Petroleum-Gas University of Ploiești, 100680 Ploiești, Romania
Naif D. Alotaibi: Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia

Mathematics, 2022, vol. 10, issue 16, 1-15

Abstract: In this paper, a novel gain-scheduled sliding-mode-type (SM-type) iterative learning (IL) control approach is proposed for the high-precision trajectory tracking of mechanical systems subject to model uncertainties and disturbances. Based on the SM variable, the proposed controller is synthesized involving a feedback regulation item, a feedforward learning item, and a robust switching item. The feedback regulation item is adopted to regulate the position and velocity tracking errors, the feedforward learning item is applied to handle the model uncertainties and repetitive disturbance, and the robust switching item is introduced to compensate the nonrepetitive disturbance and linearization residual error. Moreover, the gain-scheduled mechanism is employed for both the feedback regulation item and feedforward learning item to enhance the convergence speed. Convergence analysis illustrates that the position and velocity tracking errors can eventually regulate to zero under the proposed controller. By combining the advantages of both SM control and IL control, the proposed controller has strong robustness against model uncertainties and disturbances. Lastly, simulations and comparisons are provided to evaluate the efficiency and excellent performance of the proposed control approach.

Keywords: mechanical system; sliding-mode-type iterative learning control; trajectory tracking control; gain-scheduled mechanism (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/2227-7390/10/16/3005/pdf (application/pdf)
https://www.mdpi.com/2227-7390/10/16/3005/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:10:y:2022:i:16:p:3005-:d:893187

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().