Robust fuzzy model predictive control of discrete-time Takagi–Sugeno systems with nonlinear local models
Robust fuzzy model predictive control of discrete nonlinear systems is investigated in this paper. A recently developed Takagi-Sugeno (T-S) fuzzy approach which uses nonlinear local models is adopted to approximate the nonlinear systems. A critical issue that restricts the practical application of c...
Saved in:
Main Authors: | Teng, Long, Wang, Youyi, Cai, Wenjian, Li, Hua |
---|---|
Other Authors: | School of Electrical and Electronic Engineering |
Format: | Article |
Language: | English |
Published: |
2020
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/142450 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Efficient robust fuzzy model predictive control of discrete nonlinear time-delay systems via Razumikhin approach
by: Teng, Long, et al.
Published: (2020) -
Robust model predictive control for discrete T-S fuzzy systems with nonlinear local models
by: Teng, Long, et al.
Published: (2020) -
Fuzzy model predictive control of discrete-time systems with time-varying delay and disturbances
by: Teng, Long, et al.
Published: (2020) -
Model predictive control using segregated disturbance feedback
by: Wang, C., et al.
Published: (2013) -
Self evolving Takagi-Sugeno-Kang fuzzy neural network.
by: Nguyen Ngoc Nam
Published: (2012)