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Mixed PD-Type Iterative Learning Control Algorithm for a Class of Parabolic Singular Distributed Parameter Systems
- Source :
- IEEE Access, Vol 9, Pp 12180-12190 (2021)
- Publication Year :
- 2021
- Publisher :
- IEEE, 2021.
-
Abstract
- In this paper, the iterative learning control (ILC) problem is investigated for a class of time-invariant parabolic singular distributed parameter systems. Initially, the singular distributed parameter systems is decomposed into infinite number of singular systems based on the separation principle. Meanwhile, the slow-fast subsystems are introduced via singular value decomposition method. Then, a novel mixed PD-type ILC algorithm with finite dimension is designed for the low dimensional slow part and the corresponding convergence conditions are manifested. With the proposed controller, the output error of high dimensional fast complement can satisfy the given value instead of neglecting the effect of high dimensional modes. Furthermore, under the aforesaid ILC law and the appropriate number of the low dimensional slow part, the resulting tracking error of parabolic singular distributed parameter systems can converge to any small tracking accuracy. Finally, simulation results on the distributed building automatic temperature system verify the convergence and effectiveness of the mixed PD-type ILC algorithm.
- Subjects :
- 0209 industrial biotechnology
General Computer Science
Iterative learning control
Computer science
General Engineering
02 engineering and technology
Separation principle
separation principle
Matrix decomposition
convergence analysis
Tracking error
020901 industrial engineering & automation
singular distributed parameter systems
Dimension (vector space)
Control theory
Distributed parameter system
low dimensional slow part
Convergence (routing)
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
General Materials Science
lcsh:Electrical engineering. Electronics. Nuclear engineering
Algorithm
lcsh:TK1-9971
Subjects
Details
- Language :
- English
- ISSN :
- 21693536
- Volume :
- 9
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....acea3be784005b2a6e16a845d2aec4db