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Indirect adaptive fuzzy control of nonlinear descriptor systems
- Source :
- European Journal of Control. 51:30-38
- Publication Year :
- 2020
- Publisher :
- Elsevier BV, 2020.
-
Abstract
- This paper focuses on indirect adaptive fuzzy control of nonlinear descriptor systems described by both uncertain algebraic and differential equations aiming to guarantee asymptotic tracking of a regular and impulse-free descriptor reference model. The proposed controller exploits the universal approximation capability of Takagi–Sugeno–Kang (TSK) fuzzy models for the identification of the unknown system dynamics. More specifically, it is assumed that only the system order is known while all the dynamical equations of the system are completely unknown. In the proposed method, the asymptotic tracking of the reference model is guaranteed by suitable adaptation laws for the parameters of the TSK fuzzy model. Simulation results are presented to demonstrate the effectiveness of the proposed method.
- Subjects :
- 0209 industrial biotechnology
Computer science
Differential equation
General Engineering
02 engineering and technology
Fuzzy control system
Fuzzy logic
System dynamics
Identification (information)
020901 industrial engineering & automation
Control theory
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Equations for a falling body
Reference model
Subjects
Details
- ISSN :
- 09473580
- Volume :
- 51
- Database :
- OpenAIRE
- Journal :
- European Journal of Control
- Accession number :
- edsair.doi...........6ddd8e8c9195633db208ebe8aab1157f
- Full Text :
- https://doi.org/10.1016/j.ejcon.2019.06.007