Fault Tolerant Controller Design for a Faulty UAV Using Fuzzy Modeling Approach

Abstract

We address a fault tolerant control (FTC) issue about an unmanned aerial vehicle (UAV) under possible simultaneous actuator saturation and faults occurrence. Firstly, the Takagi-Sugeno fuzzy models representing nonlinear flight control systems (FCS) for an UAV with unknown disturbances and actuator saturation are established. Then, a normal H-infinity tracking controller is presented using an online estimator, which is introduced to weaken the saturation effect. Based on the normal tracking controller, we propose an adaptive fault tolerant tracking controller (FTTC) to solve actuator loss of effectiveness (LOE) fault problem. Compared with previous work, this approach developed in our research need not rely on any fault diagnosis unit and is easily applied in engineering. Finally, these results in simulation indicate the efficiency of our presented FTC scheme.

Sensor Fault Diagnosis Observer for an Electric Vehicle Modeled as a Takagi-Sugeno System

“…The observer TS (20) asymptotically converges to (17) if there exist matrices P = P T > 0, M i , satisfying the following matrix inequality:…”

“…In particular, it has been shown that a TS dynamic model obtained through the nonlinear sector transformation approach can describe the overall behavior of a highly complex nonlinear system with a high degree of accuracy [11,14]. As a result, its applicability in designing controllers, diagnosis systems, and observers, among others, has become of high importance; see, for instance, [15][16][17] and references therein. Applications on vehicles can be found in the literature; for example, in [4], a predictive control strategy using a TS model is presented to control the velocity in an EV, and the authors in [18] proposed a linear parameter varying (LPV) controller in order to control the tracking of the longitudinal velocity and the yaw velocity of the EV.…”