State Estimation and Dissipative-Based Control Design for Vehicle Lateral Dynamics With Probabilistic Faults

In this paper, the state estimation problem is studied for vehicle lateral dynamics, which are approximated by the Takagi-Sugeno (T-S) fuzzy model with probabilistic actuator faults. First, a fuzzy rule-based state estimator is constructed to estimate the exact state values of the considered system,...

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Bibliographic Details
Published in:IEEE transactions on industrial electronics (1982) 2018-09, Vol.65 (9), p.7193-7201
Main Authors: Sakthivel, Rathinasamy, Mohanapriya, Saminathan, Ahn, Choon Ki, Selvaraj, Palanisamy
Format: Article
Language:English
Subjects:
Actuator fault model
Actuators
Bicycles
Controllers
Dissipation
Fault tolerance
Fault tolerant systems
Feedback control
Fuzzy systems
lateral vehicle dynamics
Linear matrix inequalities
Mathematical analysis
Matrix methods
State estimation
State feedback
Statistical analysis
Takagi–Sugeno (T–S) fuzzy system
Vehicle dynamics
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Summary:In this paper, the state estimation problem is studied for vehicle lateral dynamics, which are approximated by the Takagi-Sugeno (T-S) fuzzy model with probabilistic actuator faults. First, a fuzzy rule-based state estimator is constructed to estimate the exact state values of the considered system, and then a probability-dependent fault-tolerant state feedback controller is developed based on the estimated state values. Furthermore, by constructing an appropriate Lyapunov-Krasovskii functional, some novel delay-dependent sufficient conditions that ensure the mean-square asymptotic stability and strict (Q d , S d , R d )dissipativity of the closed-loop fuzzy system are derived. Specifically, the proposed dissipative-based observer design scheme is developed by means of a set of linear matrix inequalities. Finally, the proposed state estimation and faulttolerant dissipative controller are applied to the addressed system, which demonstrates the usefulness of the developed analytical results.
ISSN:0278-0046
1557-9948
DOI:10.1109/TIE.2018.2793253