Fault Tolerant Control Design For Takagi-Sugeno Nonlinear Systems

Robust Takagi-Sugeno sensor fault tolerant control strategy for nonlinear system

Design of nonlinear parity approach to fault detection and identification based on Takagi-Sugeno fuzzy model and unknown input observer in nonlinear systems

In this study, a novel fault detection scheme is developed for a class of nonlinear system in the presence of sensor noise. A nonlinear Takagi-Sugeno fuzzy model is implemented to create multiple models. While the T-S fuzzy model is used for only the nonlinear distribution matrix of the fault and measurement signals, a larger category of nonlinear systems is considered. Next, a mapping to decou...

Predictive and robust fault-tolerant control for Takagi-Sugeno systems

The paper deals with the problem of robust predictive fault-tolerant control for nonlinear discrete-time systems described by the Takagi-Sugeno models. The proposed approach consists of three steps, i.e. it starts from fault estimation, the fault is compensated with a robust controller, and finally, when the compensation is not successful then a suitable predictive action is performed. This app...

Fault Tolerant Control for Nonlinear Systems Described by Takagi-sugeno Models

ABSTRACT: In this paper the problem of active fault tolerant control (FTC) in noisy systems is studied. The proposed FTC strategy is based on the known of the fault estimate and the error between the faulty system state and a reference system state. A proportional integral observer is used in order to estimate the state and the actuator faults. The obtained results are then extended to nonlinea...

Fault-Tolerant Model-Based Predictive Control Using Multiple Takagi-Sugeno Fuzzy Models

In this paper, we address fault-tolerant control for non-linear plants. We perform soft fault detection and isolation for partial fault detection. A new method is proposed that combines model predictive controllers with fuzzy Takagi-Sugeno models. An example is presented to illustrate the functionality of the proposed approach. Keywords— Fault detection and isolation, multiple models, fuzzy Tak...