Anti-disturbance tracking control for systems with nonlinear disturbances using T–S fuzzy modeling
| Autor: | Tianping Zhang, Xiang Xiang Fan, Yang Yi |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
0209 industrial biotechnology
Mathematical optimization Disturbance (geology) Cognitive Neuroscience 02 engineering and technology Tracking (particle physics) Fuzzy logic Computer Science Applications Tracking error Nonlinear system 020901 industrial engineering & automation Artificial Intelligence Control theory Control system Convex optimization Convergence (routing) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Mathematics |
| Zdroj: | Neurocomputing. 171:1027-1037 |
| ISSN: | 0925-2312 |
| DOI: | 10.1016/j.neucom.2015.07.039 |
| Popis: | This paper addresses a novel anti-disturbance dynamical tracking problem for a class of MIMO systems subject to unknown disturbances and nonlinear dynamics. Different from some traditional anti-disturbance results, T-S fuzzy models are firstly employed to describe the nonlinear disturbances, in which a disturbance observer based on T-S exogenous models is designed under different conditions to estimate the unknown nonlinear disturbances for the plants with known and unknown nonlinearities, respectively. By integrating the estimates of disturbance with PI-type control input, a composite controller based on convex optimization theory is proposed to ensure the system stability and convergence of the tracking error to zero. Meanwhile, the favorable disturbance estimation and attenuation performance can also be achieved by the designed convex optimization algorithm. Finally, the effectiveness of the proposed control schemes is verified by simulations for flight control systems with three different types of nonlinear disturbances. |
| Databáze: | OpenAIRE |
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