Two‐stage Kalman filter‐based actuator/surface fault identification and reconfigurable control applied to F‐16 fighter dynamics

Abstract

In this study, an active fault-tolerant control technique with reconfiguration against actuator/surface failures is presented. A two-stage Kalman filter is designed in order to identify the control distribution matrix elements that correspond to the faulty actuator/surface; thus, the control reconfiguration is carried out using this identified control distribution matrix. The actuator/surface fault identification problem is solved through two jointly operating Kalman filters: the first one is for the estimation of the control distribution matrix elements that correspond to the faulty actuator/surface, and the second one is for the estimation of the state variables of the aircraft model.A structure for the active fault-tolerant aircraft flight control system with reconfiguration against actuator/surface failures is presented. A control reconfiguration action is taken in order to keep the performance of the impaired aircraft the same as that of the unimpaired aircraft.In simulations, the nonlinear flight dynamics of an AFTI/F-16 fighter model is considered, and the performance of the proposed actuator/surface failure identification and reconfigurable control schemes are examined for this model.The active fault-tolerant control systems consist of two basic subsystems [9]:1. fault detection and isolation (FDI) or system identification and 2. control reconfiguration or restructure.In an active fault-tolerant control system, faults are detected and identified by an FDI scheme, and the controllers are reconfigured accordingly online in real time. An effective FDI procedure is critical for designing high-performance active fault-tolerant control systems. Many model-based FDI techniques have been developed to detect and identify the sensor and actuator faults via the analytical redundancy, state estimation, and parameter identification approaches [7,[10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25].The works [26-28] address the control allocation problem for a nonlinear over-actuated timevarying system where parameters affine in the actuator model may be assumed unknown. In order to cope with an unknown parameter vector in the actuator model, an adaptive law is defined. The parameter estimate is used in the control allocation algorithm, and a certainty equivalent adaptive optimal control allocation can be defined. But these works do not mention FDI techniques.Under the assumption that system faults can be detected, isolated, and identified via FDI techniques, several reconfigurable control methods have been developed in the literature. Existing reconfigurable controller design methods are based on one of the following approaches: linear quadratic regulator (LQR) [5,29], model following [30,31], adaptive control [32,33], pseudoinverse [17,34,35], multiple model [32,[36][37][38][39], eigenstructure assignment [6,40,41], model predictive control [42], and neural networks [43][44][45]. However, most methods assume that a perfect post-fault model of the system is known and the post-fault system model is not know...

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