Integrated design of fault-tolerant control for nonlinear systems based on fault estimation and T-S fuzzy modelling
Lan, Jianglin; Patton, Ron J.
Professor Ron Patton R.J.Patton@hull.ac.uk
Professor of Control and Intelligent Systems Engineering
This paper proposes an integrated design of faulttolerant control (FTC) for nonlinear systems using Takagi-Sugeno (T-S) fuzzy models in the presence of modelling uncertainty along with actuator/sensor faults and external disturbance. An augmented state unknown input observer is proposed to estimate the faults and system states simultaneously, and using the estimates an FTC controller is developed to ensure robust stability of the closed-loop system. The main challenge arises from the bi-directional robustness interactions since the fault estimation (FE) and FTC functions have an uncertain effect on each other. The proposed strategy uses a single-step linear matrix inequality formulation to integrate together the designs of FE and FTC functions to satisfy the required robustness. The integrated strategy is demonstrated to be effective through a tutorial example of an inverted pendulum system (based on robust T-S fuzzy designs).
|Journal Article Type||Article|
|Journal||IEEE transactions on fuzzy systems|
|Publisher||Institute of Electrical and Electronics Engineers|
|Peer Reviewed||Peer Reviewed|
|APA6 Citation||Lan, J., & Patton, R. J. (2017). Integrated design of fault-tolerant control for nonlinear systems based on fault estimation and T-S fuzzy modelling. IEEE Transactions on Fuzzy Systems, 25(5), 1141-1154. https://doi.org/10.1109/tfuzz.2016.2598849|
|Keywords||Integrated fault-tolerant control; Augmented state unknown input observer; Nonlinear systems; T-S fuzzy systems|
|Copyright Statement||This is the accepted version of an article accepted for publication in: IEEE transactions on fuzzy systems, 2016, v.25 issue 5.|
|Additional Information||This is the accepted version of an article accepted for publication in: IEEE transactions on fuzzy systems, 2016, v.25 issue 5.|
This is the accepted version of an article accepted for publication in: IEEE transactions on fuzzy systems, 2016, v.25 issue 5.
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