2007
DOI: 10.1109/fuzzy.2007.4295338
|View full text |Cite
|
Sign up to set email alerts
|

Supervised Adaptive PID Control of Unknown Nonlinear Systems Using Fuzzily Blended Time-Varying Canonical Model

Abstract: This paper proposes a supervised PID adaptive control scheme for unknown nonlinear systems to enhance system robustness in the face of external disturbances, variation in system parameters, and parameter drift in the adaptation law. The supervising controller is designed based on an on-line identified model in a fuzzily blended time-varying canonical form. The model largely simplifies the identification of the nonlinear plant, and the design of both the supervising controller and the adaptation law. Numerical … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2

Citation Types

0
2
0

Year Published

2009
2009
2021
2021

Publication Types

Select...
1
1

Relationship

1
1

Authors

Journals

citations
Cited by 2 publications
(2 citation statements)
references
References 10 publications
0
2
0
Order By: Relevance
“…In [15] we proposed a supervised adaptive PID control scheme based on the on-line identification of time-varying nonlinear plants. The model used to identify the unknown plants is in a fuzzily blended and time-varying canonical form [16].…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…In [15] we proposed a supervised adaptive PID control scheme based on the on-line identification of time-varying nonlinear plants. The model used to identify the unknown plants is in a fuzzily blended and time-varying canonical form [16].…”
Section: Introductionmentioning
confidence: 99%
“…In this paper, the scheme of [15] is extended for nonlinear systems with significant time delays. Specifically, a time-delay neural model is used in the inner-loop adaptive controller.…”
Section: Introductionmentioning
confidence: 99%