Actuator fault detection and performance recovery with Kalman filter-based adaptive observer

Abstract

A novel Kalman filter-based adaptive observer for the sampled-data nonlinear time-varying system is proposed in this paper. With the high gain property of Kalman filter, it is applicable to a large variation of unknown parameters, which can be estimated optimally. Then a method of actuator fault detection is proposed. With the estimated faults, one can use the proposed input compensation method to solve actuator faults. Additionally, the optimal linearization technique is used to obtain the locally optimal linear model for a nonlinear system at each sampled state, so that the actuator fault detection and performance recovery of a sampled-data nonlinear time-varying system is accomplished. In this paper, we also introduce a prediction-based digital redesign method to develop the corresponding sampled-data controller.

Sequencing Optimization ink-out-of-nCold-Standby Systems Considering Mission Cost

“…Introduction Among the various system designs for achieving fault tolerance, the k-out-of-n standby redundancy system structure has become a popular type since it was first introduced by Birnbaum, Esary and Saunders (1961). To date, it has found a wide range of applications in both industrial and military systems (Becker and Hansen 1983;Golay, Seong and Manno 1989;Tsai et al 2007;Amari, Zuo and Dill 2008;Amari and Pham 2010). Specific examples include airplanes with multi-engine systems, cables in a bridge, a data processing system with multiple video displays, and communication systems with multiple transmitters (Amari, Zuo and Dill 2008;Amari and Pham 2010).…”

Cooperative actuator fault accommodation in formation flight of unmanned vehicles using absolute measurements

“…Moreover, a fault-tolerant control scheme has been developed by using estimates of the descriptor states and faults and linear matrix-inequality (LMI) techniques. In [18], an adaptive Kalman filtering algorithm is developed to estimate the reduction of the control effectiveness in a closed-loop setting. The state estimates are fed back to achieve the steady-state regulation, while the fault effectiveness estimate is used for the on-line tuning of the control law.…”

“…Various methods have been proposed in the literature [16][17][18][19][20][21][22][23] for the problem of fault diagnosis, identification and recovery (FDIR) of a single unmanned vehicle. However, none of these works have properly introduced and investigated the concept of cooperative fault accommodation in formation flight of unmanned vehicles.…”

Three-stage Kalman filter for state and fault estimation of linear stochastic systems with unknown inputs

“…In this context, this problem has been extensively studied using the Kalman filtering approach, see e.g. [1-9, [13][14][15][16][17][18][19][20][21][22][23][24].…”